Method and System for Providing Enhanced Location Based Information for Wireless Handsets

ABSTRACT

Methods, devices and systems for generating enhanced location information on or about a mobile device may include hybrid lateration and trilateration solutions in which the mobile device performs location determination calculations with the aid of network components or global positioning systems (GPS). Mobile devices may automatically form groups based on proximity and/or may be grouped together via a network server. Mobile devices in a group may share computed location information and/or information collected from internal sensors with other grouped mobile devices. Information shared between grouped mobile devices may be used to enhance the location information computed on each mobile device. For example, each mobile device may supplement and/or augment previously computed location information based on the received location information and/or relative positions of other mobile devices in the same group. Each mobile device may also utilize local sensors to further enhance their location information.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/690,713 entitled “Method and System for Providing Enhanced LocationBased Information for Wireless Handsets” filed on Apr. 20, 2015, whichis a continuation in part of U.S. patent application Ser. No. 14/293,056entitled “Method and System for Providing Enhanced Location BasedInformation for Wireless Handsets” filed on Jun. 2, 2014, which is acontinuation of U.S. patent application Ser. No. 13/585,125 entitled“Method and System for Providing Enhanced Location Based Information forWireless Handsets” filed Aug. 14, 2012, and which claims the benefit ofpriority of U.S. Provisional Application No. 61/575,300, entitled“Method and System for Providing Enhanced Location Based Information forWireless Handsets” filed Aug. 18, 2011, and U.S. Provisional ApplicationNo. 61/573,636, entitled “Method and System for Providing EnhancedLocation Based Information for Wireless Handsets” filed Sep. 9, 2011,the entire contents of all of which are hereby incorporated byreference.

FIELD OF INVENTION

The present application relates generally to a wireless mobilecommunication system, and more particularly to methods and systems thatprovide enhanced location information for wireless mobile devices.

BACKGROUND

Wireless communication technologies and mobile electronic devices (e.g.,cellular phones, tablets, laptops, etc.) have grown in popularity anduse over the past several years. To keep pace with increased consumerdemands, mobile electronic devices have become more powerful and featurerich, and now commonly include global positioning system (GPS)receivers, sensors, and many other components for connecting users tofriends, work, leisure activities and entertainment. However, despitethese advancements, mobile devices remain lacking in their ability toprovide effective location based services, information, orcommunications. As mobile devices and technologies continue to grow inpopularity and use, generating enhanced location information for mobiledevices is expected to become an important and challenging designcriterion for mobile device manufactures and network engineers.

SUMMARY

The methods and apparatuses of various embodiments provide devices,circuits and methods for precise location determination inmulti-technology communications devices. Embodiment methods may includedetermining, by a processor of the mobile device, an initial position ofthe mobile device, generating local position information, generatingexternal position information based on location information receivedfrom an external location tracking system; generating proximity positioninformation based on distance information received via the antenna froma second mobile device, generating final location information based onthe determined initial position, the generated local positioninformation, the generated external position information, and thegenerated proximity position information, and using the generated finallocation information set to provide a location based service.

In some embodiments, the final location estimation set may include aposition, a velocity and an acceleration, each having a latitudecomponent, a longitude component, and an altitude component. In suchembodiments, generating any of the local position information, theexternal position information, or the proximity position information mayfurther include separating, by the processor, location information intoa set of latitude components, a set of longitude components, and a setof altitude components; and executing, by the processor, a kalman filteron each of the set of latitude components, the set of longitudecomponents, and the set of altitude components to produce positioninformation. Such embodiments may include, determining an errorassociated with generation of the position information.

Some embodiments may include, updating the local position informationafter a predetermined time interval to produce updated local positioninformation; updating the external position information after apredetermined time interval to produce updated external positioninformation; and updating proximity position information after apredetermined time interval to produce updated proximity positioninformation. Such embodiments may include updating the final locationestimation set based on the updated local position information, theupdated external position information, the updated proximity positioninformation and the final location estimation set to produce an updatedfinal location estimation set. Alternatively, in such embodiments,updating any of the local position information, external positioninformation, or proximity position information may include determiningwhether updated location information or updated distance information isavailable, combining current location information or current distanceinformation with an error value, in response to determining that updatedlocation information or updated distance information is not available.In another alternative of such embodiments, the predetermined intervalmay be a time interval between successive determinations of the localposition information.

In some embodiments, the distance information may comprise a distancefrom the mobile device to the second mobile device.

In some embodiments, the local position information may be obtainedusing dead reckoning.

In some embodiments, local position information may be obtained usingcombination of local sensor outputs.

In some embodiments, the external location tracking system may be aglobal positioning (GPS).

Embodiments include a multi-technology communication device having oneor more processors or processor cores configured withprocessor-executable instructions to perform operations of one or moreof the embodiment methods described above.

Embodiments include a non-transitory processor-readable medium havingstored thereon processor-executable software instructions to cause aprocessor to perform operations of one or more of the embodiment methodsdescribed above.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated herein and constitutepart of this specification, illustrate exemplary embodiments of theinvention, and, together with the general description given above andthe detailed description given below, serve to explain features of theinvention.

FIG. 1 is a communication system block diagram illustrating networkcomponents of an example telecommunication system suitable for use in amobile-device centric approach for determining the location of a mobiledevice in accordance with various embodiments.

FIG. 2 is a communication system block diagram illustrating networkcomponents of an example telecommunication system suitable for use in anetwork centric approach for determining the location of a mobile devicein accordance with various embodiments.

FIG. 3 is an illustration of an example mobile device suitable for usein grouping with other mobile devices and computing precise locationinformation in accordance with the various embodiments.

FIG. 4A is a communication system block diagram illustrating networkcomponents of an example LTE communication system suitable for use withvarious embodiments

FIG. 4B is a block diagram illustrating logical components,communication links and information flows in an embodiment communicationsystem.

FIGS. 5A-5C are component block diagrams illustrating functionalcomponents, communication links, and information flows in an embodimentmethod of grouping mobile devices and sharing location informationbetween grouped mobile devices.

FIG. 5D is a process flow diagram illustrating an embodiment mobiledevice method for grouping mobile devices and sharing locationinformation between grouped mobile devices and the network to computeenhanced location information.

FIGS. 6A-6D are component block diagrams illustrating functionalcomponents, communication links, and information flows in an embodimentmethod for computing location information in which the grouped/pairedmobile devices are updated with their respective location information.

FIG. 6E is a process flow diagram illustrating an embodiment systemmethod of determining the location of two or more grouped mobiledevices.

FIG. 6F is a process flow diagram illustrating an embodiment mobiledevice method of adjusting the update intervals in response to detectinga low battery condition.

FIG. 7 is a component block diagram illustrating functional components,communication links, and information flows in embodiment method ofperiodically scan for cells.

FIG. 8 is a process flow diagram illustrating an embodiment mobiledevice method for determining the location of a mobile device in awireless network.

FIGS. 9A-9E are component block diagrams illustrating various logicaland functional components, information flows and data suitable for usein various embodiments.

FIG. 10 is a sequence diagram illustrating an embodiment hybridlateration method by which mobile devices may calculate positionaccurately with the help of the network.

FIG. 11 is a sequence diagram illustrating another embodiment hybridlateration method in which a mobile device cannot locate a network duecoverage problems.

FIGS. 12A-12C are component block diagrams illustrating functionalcomponents, communication links, and information flows in an embodimentmethod of transferring a connection from a local radio system to thesmall cell system.

FIGS. 13A-13C are component block diagrams illustrating functionalcomponents, communication links, and information flows in an embodimentmethod of identifying and responding to a distressed mobile device.

FIG. 14 is a component block diagrams illustrating functionalcomponents, communication links, and information flows in an embodimentmethod of performing dead reckoning grouping mobile devices in an ad-hocscheme.

FIG. 15 is a process flow diagram illustrating an embodiment mobiledevice method for determining the location of a mobile device.

FIGS. 16A-B are process flow diagrams illustrating an embodiment methodsof obtaining position information for a mobile device in a wirelessnetwork.

FIG. 17 is a process flow diagram illustrating an embodiment method ofupdating location information in the absence of new locationmeasurements.

FIG. 18 is a process flow diagram illustrating an embodiment method toproduce precise location information.

FIG. 19 is a component block diagram of a mobile device suitable for usewith an embodiment.

FIG. 20 is a component block diagram of a server suitable for use withan embodiment.

DETAILED DESCRIPTION

The various embodiments will be described in detail with reference tothe accompanying drawings. Wherever possible, the same reference numberswill be used throughout the drawings to refer to the same or like parts.References made to particular examples and implementations are forillustrative purposes, and are not intended to limit the scope of theinvention or the claims.

The word “exemplary” is used herein to mean “serving as an example,instance, or illustration.” Any implementation described herein as“exemplary” is not necessarily to be construed as preferred oradvantageous over other implementations.

The terms “mobile device,” “cellular telephone,” and “cell phone” areused interchangeably herein to refer to any one or all of cellulartelephones, smartphones, personal data assistants (PDA's), laptopcomputers, tablet computers, ultrabooks, palm-top computers, wirelesselectronic mail receivers, multimedia Internet enabled cellulartelephones, wireless gaming controllers, and similar personal electronicdevices which include a programmable processor, a memory and circuitryfor sending and/or receiving wireless communication signals. While thevarious embodiments are particularly useful in mobile devices, such ascellular telephones, which have limited battery life, the embodimentsare generally useful in any computing device that may be used towirelessly communicate information.

The terms “wireless network”, “network”, “cellular System”, “cell tower”and “radio access point” may used generically and interchangeably torefer to any one of various wireless mobile systems. In an embodiment,wireless network may be a radio access point (e.g., a cell tower), whichprovides the radio link to the mobile device so that the mobile devicecan communicate with the core network.

A number of different cellular and mobile communication services andstandards are available or contemplated in the future, all of which mayimplement and benefit from the various embodiments. Such services andstandards include, e.g., third generation partnership project (3GPP),long term evolution (LTE) systems, third generation wireless mobilecommunication technology (3G), fourth generation wireless mobilecommunication technology (4G), global system for mobile communications(GSM), universal mobile telecommunications system (UMTS), 3GSM, generalpacket radio service (GPRS), code division multiple access (CDMA)systems (e.g., cdmaOne, CDMA2000™), enhanced data rates for GSMevolution (EDGE), advanced mobile phone system (AMPS), digital AMPS(IS-136/TDMA), evolution-data optimized (EV-DO), digital enhancedcordless telecommunications (DECT), Worldwide Interoperability forMicrowave Access (WiMAX), wireless local area network (WLAN), publicswitched telephone network (PSTN), Wi-Fi Protected Access I & II (WPA,WPA2), Bluetooth®, integrated digital enhanced network (iden), and landmobile radio (LMR). Each of these technologies involves, for example,the transmission and reception of voice, data, signaling and/or contentmessages. It should be understood that any references to terminologyand/or technical details related to an individual telecommunicationstandard or technology are for illustrative purposes only, and are notintended to limit the scope of the claims to a particular communicationsystem or technology unless specifically recited in the claim language.

A number of different methods, technologies, solutions, and/ortechniques (herein collectively “solutions”) are currently available fordetermining the location of mobile device, any or all of which may beimplemented by, included in, and/or used by the various embodiments.Such solutions include, e.g., global positioning system (GPS) basedsolutions, assisted GPS (A-GPS) solutions, and cell-based positioningsolutions such as cell of origin (COO), time of arrival (TOA), observedtime difference of arrival (OTDOA), advanced forward link trilateration(AFLT), and angle of arrival (AOA). In various embodiments, suchsolutions may implemented in conjunction with one or more wirelesscommunication technologies and/or networks, including wireless wide areanetworks (WWANs), wireless local area networks (WLANs), wirelesspersonal area networks (WPANs), and other similar networks ortechnologies. By way of example, a WWAN may be a Code Division MultipleAccess (CDMA) network, a Frequency Division Multiple Access (FDMA)network, an OFDMA network, a 3GPP LTE network, a WiMAX (IEEE 802.16)network, and so on. The WPAN may be a Bluetooth network, an IEEE 802.15xnetwork, and so on. A WLAN may be an IEEE 802.11x network, and so on. ACDMA network may implement one or more radio access technologies (RATs)such as CDMA2000, Wideband-CDMA (W-CDMA), and so on.

Various embodiments discussed herein may generate, compute, and/or makeuse of location information pertaining to one or more mobile devices.Such location information may be useful for providing and/orimplementing a variety of location-based services, including emergencylocation services, commercial location services, internal locationservices, and lawful intercept location services. By way of example:emergency location services may include services relating to theprovision of location and/or identification information to emergencyservice personal and/or emergency systems (e.g., to 911 system);commercial location services may include any general or value-addedservice (e.g., asset tracking services, navigation services,location-based advertising services, etc); internal location servicesmay include services pertaining to the management of the wirelessservice provider network (e.g., radio resource management services,message delivery services, paging services, call delivery services,services for providing position/location network enhancements, etc.);and lawful intercept location services may include any service thatprovides public safety and/or law enforcement agencies withidentification and/or location information pertaining to a mobile deviceor a mobile device user. While the various embodiments are particularlyuseful in applications that fall within one or more of thecategories/types of location based services discussed above, theembodiments are generally useful in any application or service thatbenefits from location information.

Modern mobile electronic devices (e.g., mobile phones) typically includeone or more geospatial positioning systems/components for determiningthe geographic location of the mobile device. Location informationobtained by these geospatial systems may be used by location-awaremobile software applications (e.g., Google® Maps, Yelp®, Twitter®Places, “Find my Friends” on Apple®, etc.) to provide users withinformation regarding the mobile device's physical location at a givenpoint in time. In recent years, such location-based services andsoftware applications have increased in popularity and use, and nowenable mobile device users to navigate cities, read reviews of nearbyrestaurants and services, track assets or friends, obtain location-basedsafety advice, and/or take advantage of many other location-basedservices on their mobile devices.

Consumers of modern mobile devices now demand more advanced, robust, andfeature-rich location-based services than that which is currentlyavailable on their mobile devices. However, despite many recent advancesin mobile and wireless technologies, mobile devices remain lacking intheir ability to provide their users/consumers with location basedservices that are accurate or powerful enough to meet the demands ofthese consumers. For example, while existing location-aware mobilesoftware applications (e.g., “Find my Friends” on Apple®, Google®Latitude, etc.) enable a mobile device user to view the approximategeographical position of other mobile devices on a two-dimensional map,they lack the capability to accurately, efficiently and consistently pinpoint the precise location and/or position of the other mobile devicesin all three dimensions and/or within a wireless communication network.The various embodiments overcome these and other limitations of existingsolutions by collecting information from multiple mobile devices,generating more precise location information on or about one or moremobile devices, generating advanced three-dimensional location andposition information on or about one or more mobile devices, and usingthe generated location/position information to provide mobile deviceusers with more accurate, more powerful, and more reliable locationbased services.

One of the challenges associated with using geo-spatial positioningtechnology on a mobile device is that the mobile device's ability toacquire satellite signals and navigation data to calculate itsgeospatial location (called “performing a fix”) may be hindered when themobile device is indoors, below grade, and/or when the satellites areobstructed (e.g., by tall buildings, etc.). The presence of physicalobstacles, such as metal beams or walls, may cause multipathinterference and signal degradation of the wireless communicationsignals when the mobile device is indoors or in urban environments thatinclude tall buildings or skyscrapers. In rural environments, the mobiledevice may not have sufficient access to satellite communications (e.g.,to a global positioning system satellite) to effectively ascertain themobile device's current location. These and other factors often causeexisting geo-spatial technologies to function inaccurately and/orinconsistently on mobile devices, and hinder the mobile device user'sability to fully utilize location-aware mobile software applicationsand/or other location based services and applications on his/her mobiledevice.

Another problem with using existing geo-spatial positioning technologiesis that position accuracy afforded by existing technologies is notsufficient for use in emergency services due to the relatively highlevel of position accuracy required by these services.

The various embodiments include improved location determinationsolutions that determine the location of a mobile device at the level ofposition accuracy which is suitable for use in emergency locationservices, commercial location services, internal location services, andlawful intercept location services.

Generally, there are three basic approaches for determining the locationof mobile devices in a communication network: a mobile-device centricapproach, a network centric approach and a hybrid approach that mayinclude aspects of both the mobile device centric approach and thenetwork centric approach.

FIG. 1 illustrates an example communication system 100 suitable forimplementing a mobile-device centric approach for determining thelocation of a mobile device 102 in accordance with various embodiments.The mobile device 102 may include a global positioning system (GPS)receiver in communication with multiple geo-spatial positioning andnavigation satellites 110 and a base tower 104 of a communicationnetwork 106. The mobile device 102 may receive (e.g., via the GPSreceiver) radio signals emitted by the satellites 110, measure the timerequired for the signals to reach the mobile device 102, and usetrilateration techniques to determine the geographical coordinates(e.g., latitude and longitude coordinates) of the mobile device 102. Themobile device 102 may send the geographical coordinates to thecommunication network 106 at various times and/or in response to variousconditions or events, such as upon initial acquisition with thecommunication network 106, in response to network-based requests, inresponse to third party requests, etc.

In an embodiment, the communication network may be a cellular telephonenetwork. A typical cellular telephone network includes a plurality ofcellular base stations 104 coupled to a network operations center 108,which operates to connect voice and data calls between mobile devices102 (e.g., mobile phones) and other network destinations, such as viatelephone land lines (e.g., a POTS network, not shown) and the Internet114. Communications between the mobile devices 102 and the cellulartelephone network 11 may be accomplished via two-way wirelesscommunication links, such as 4G, 3G, CDMA, TDMA, and other cellulartelephone communication technologies. The network 106 may also includeone or more servers 112 coupled to or within the network operationscenter 108 that provide connections to the Internet 114.

In various embodiments, the mobile device 102 may be configured tocommunicate with a radio access node, which can include any wirelessbase station or radio access point such as LTE, CDMA2000/EVDO,WCDMA/HSPA, IS-136, GSM, WiMax, WiFi, AMPS, DECT, TD-SCDMA, or TD-CDMAand switch, Land Mobile Radio (LMR) interoperability equipment, asatellite Fixed Service Satellite (FSS) for remote interconnection tothe Internet and PSTN.

FIG. 2 illustrates an example communication system 200 suitable forimplementing a network centric approach for determining the location ofa mobile device 102 in accordance with various embodiments. The mobiledevice 102 may include a circuitry for wirelessly sending and receivingradio signals. The communication system 200 may include a plurality ofradio access points 204, 206 having installed thereon additional radioequipment 208 for measuring the location of the mobile devices in thecommunication system. For example, the mobile device 102 may transmitradio signals for reception by one or more (e.g., typically three) radioaccess points 204, and the radio access points may receive thetransmitted signals and measure the signal strength and/or radio energyof the received signals to identify the location of the mobile device102.

In an embodiment, the radio access points 204 may be configured todetermine the location of the mobile device relative to a known locationof a network component, such as the illustrated radio access point 206.In this manner, the additional radio equipment 208 installed on theradio access points 204, 206 provides the communication system 200 withsimilar functionality as is provided by a GPS receiver for signalsreceived from the mobile device. For example, the radio equipment on oneor more of the radio access points 204 may measure how long it takes forthe radio signal to travel from the mobile device 102 to another radioaccess point 206, and using trilateration techniques (e.g., time ofarrival, angle of arrival, or a combination thereof), the mobile device102 or a network server 210 may estimate the location of the mobiledevice 102 to within an accuracy of 100 to 300 meters. Once the networkhas estimated the latitude and longitude coordinates of the mobiledevice 102, this information may be used to determine the geo-spatiallocation of the mobile device 102, which may be communicated to othersystems, servers or components via the Internet 114.

Various embodiments may implement and/or make use of a hybrid approachfor determining the location of mobile devices in a communicationnetwork, which may include aspects of both the device-centric and thenetwork-centric approaches discussed above with reference to FIGS. 1 and2. For example, an embodiment system, mobile device or network component(e.g., severs, radio access points, etc.) may be configured to implementa hybrid approach in which dead reckoning (also known as “deducedreckoning”) techniques, GPS capabilities of the mobile device, andmobile-to-mobile (i.e., mobile device to mobile device) trilateration toproduce position estimates of increased accuracy. In another embodiment,the system, devices and/or components may be configured to implement ahybrid approach in which the GPS capabilities of mobile devices, themeasured signal strengths and/or radio energy of radio signalstransmitted from the mobile devices, and known locations of networkcomponents may be used in combination to estimate the locations of oneor more mobile devices in the network. In a further embodiment, system,devices and/or components may be configured to dynamically determine thefactors (e.g., radio signal strength, GPS, etc.) to measure and/or usein determining the location of the mobile devices.

FIG. 3 illustrates sample components of a mobile device 102 in the formof a phone that may be used with the various embodiments. The phone mayinclude a speaker 304, user input elements 306, microphones 308, anantenna 312 for sending and receiving electromagnetic radiation, anelectronic display 314, a processor 324, a memory 326 and other wellknown components of modern electronic devices.

The phone may also include one or more sensors 310 for monitoringphysical conditions (e.g., location, motion, acceleration, orientation,altitude, etc.). The sensors may include any or all of a gyroscope, anaccelerometer, a magnetometer, a magnetic compass, an altimeter, anodometer, and a pressure sensor. The sensors may also include variousbio-sensors (e.g., heart rate monitor, body temperature sensor, carbonsensor, oxygen sensor, etc.) for collecting information pertaining toenvironment and/or user conditions. The sensors may also be external tothe mobile device and paired or grouped to the mobile device via a wiredor wireless connection (e.g., Bluetooth®, etc.). In embodiment, themobile device 102 may include two or more of the same type of sensor(e.g., two accelerometers, etc.).

The phone may also include a GPS receiver 318 configured to receive GPSsignals from GPS satellites to determine the geographic location of thephone. The phone may also include circuitry 320 for transmittingwireless signals to radio access points and/or other network components.The phone may further include other components/sensors 322 fordetermining the geographic position/location of the phone, such ascomponents for determining the radio signal delays (e.g., with respectto cell-phone towers and/or cell sites), performing trilateration and/ormultilateration operations, identifying proximity to known networks(e.g., Bluetooth® networks, WLAN networks, WiFi, etc.), and/or forimplementing other known geographic location technologies.

The phone may also include a system acquisition function configured toaccess and use information contained in a subscriber identity module(SIM), universal subscriber identity module (USIM), and/or preferredroaming list (PRL) to, for example, determine the order in which listedfrequencies or channels will be attempted when the phone is toacquire/connect to a wireless network or system. In various embodiments,the phone may be configured to attempt to acquire network access (i.e.,attempt to locate a channel or frequency with which it can access thewireless/communication network) at initial power-on and/or when acurrent channel or frequency is lost (which may occur for a variety ofreasons).

The phone may include pre-built in USIM, SIM, PRL or access pointinformation. In an embodiment, the mobile device may be configured forfirst responders and/or public safety network by, for example, settingthe incident radio system as the default and/or preferred communicationsystem.

As mentioned above, despite recent advances in mobile and wirelesscommunication technologies, determining the specific location of amobile device 102 in a wireless network remains a challenging task for avariety of reasons, including the variability of environmentalconditions in which mobile devices are often used by consumers,deficiencies in existing technologies for computing and/or measuringlocation information on mobile devices, and the lack of uniformstandards. For example, there is currently no universally acceptedstandard for implementing or providing location-based services. As aresult, mobile device designers and wireless network operators, inconjunction with local public safety and third party providers, areusing a variety of inefficient, incoherent, and sometimes incompatiblemethods, technologies, solutions, and/or techniques to determine thelocation of a mobile device and/or to provide location based services.

While there are no universally accepted standards for implementing orproviding location-based services, there are certain requirements orstandards associated with determining the location of a mobile devicethat may be of use in various embodiments. The U.S. Congress hasmandated that cellular service providers configure their networks,communication systems and/or mobile devices so that the locations ofmobile devices can be determined when a 911 call is placed. To implementCongress's mandate, the Federal Communications Commission (FCC)requested cellular service providers upgrade their systems in two phases(herein “Phase I” and “Phase II” respectively). While the level ofprecision/accuracy provided by these Phase I and II upgrades aregenerally inadequate for providing effective location based servicesthat meet the demands of modern users of mobile devices, these upgradesprovide a foundation from which more effective location based solutionsmay be built.

As mentioned above, the FCC requested cellular service providers upgradetheir systems in two phases. In the first phase (Phase I), cellularservice providers were to upgrade their systems so that emergency calls(e.g., 911 calls) are routed to the public service answering point(PSAP) closest to the cell-tower antenna with which the mobile device isconnected, and so that PSAP call-takers can view the phone number of themobile device and the location of the connecting cell-tower. Thelocation of the connecting cell-tower may be used to identify thegeneral location of the mobile device within a 3-6 mile radius.

In the second phase (Phase II), cellular service providers were toupgrade their systems so that PSAP call-takers could identify thelocation of the mobile device to within 300 meters. To meet these PhaseII requirements, wireless service providers have implemented a varietyof technologies, and depending on the technology used, can generallyidentify the location of the mobile device to within 50-300 meters. Forexample, on systems that have implemented a network-based solution(e.g., triangulation of nearby cell towers, etc.), the location of amobile device can be determined within an accuracy of 100 meters 67% ofthe time, and to within an accuracy of 300 meters 95% of the time. Onsystems that have adopted a mobile device-based solution (e.g., embeddedglobal positioning system receivers, etc.), the location of the mobiledevice may be determined to within 50 meters 67% of the time, and towithin 150 meters 95% of the time.

Existing phase I and II solutions, alone, are not adequate forgenerating location information having sufficient accuracy or detail foruse in providing accurate, powerful, and reliable location basedservices. Various embodiments may use some or all of the capabilitiesbuilt into existing systems (e.g., as part of phase I and II upgrades,device-centric systems, network-centric systems, etc.), in conjunctionwith more advanced location determination techniques, to computelocation information suitable for the advanced location based servicesdemanded by today's consumers.

In addition to the three basic approaches discussed above, a number ofdifferent solutions are currently available for determining the locationof mobile device, any or all of which may be implemented by and/orincluded in the various embodiments.

Most conventional location determination solutions use distanceestimation techniques that are based on single-carrier signals, and oneof the fundamental operations in ground-based (or network-centric)location determination solutions is timing estimation of a first-arrivalpath of a signal. That is, a single-carrier signal transmitted between atransceiver and a mobile device can be received via multiple paths(i.e., multipath), and the multiple paths of the signal can havedifferent received powers and arrival times. The received signal may becross-correlated to distinguish the multiple paths of the receivedsignal. In this method, it is generally assumed that the first-arrivalpath (e.g., first detected signal, strongest signal, etc.) is associatedwith the path traveling the shortest distance, and hence is the rightvalue to use in estimating distance between the mobile device and thetransceiver. Often, this first-arrival path is the strongest path due tozero or fewer reflections, relative to the other paths, between thetransceiver and the mobile device.

In various embodiments, the first-arrival time of the identifiedfirst-arrival path may be used in addition to other parameters (e.g., anestimated signal transmission time and/or a time offset between clocksof the transceiver and the mobile device, etc.) to estimate distancebetween a mobile device and a network component (e.g., another mobiledevice, a transceiver, an access point, a base station, etc.). Thefirst-arrival time may be estimated by the mobile device (e.g., based onthe downlink received signal) or by the network component (e.g., basedon an uplink received signal).

The location of the mobile device may also be determined by estimatingthe distance between the mobile device and a network component or othersignal sources (e.g., a transceiver, ground or satellite-based signalsources, etc.). For example, the location of the mobile device may bedetermined by performing trilateration using estimated distances betweenmultiple (e.g., three or more) transceivers and the mobile device.

Another location determination solution may include computing anobserved time difference of arrival (OTDOA) value by measuring thetiming of signals received from three network components (e.g., mobiledevices, transceivers, access points, etc.). For example, a mobiledevice may be configured to compute two hyperbolas based on a timedifference of arrival between a reference transceiver signal and signalsof two neighbor transceivers. The intersection of the computedhyperbolas may define a position on the surface of the earth that may beused by various embodiments to determine the location of the mobiledevice.

The accuracy of such OTDOA solutions may be a function of the resolutionof the time difference measurements and the geometry of the neighboringtransceivers. As such, implementing an OTDOA solution may requiredetermining the precise timing relationship between the neighboringtransceivers. However, in existing asynchronous networks, this precisetiming relationship may be difficult to ascertain.

In various embodiments, location measurement units (LMUs) may be addedthroughout a deployment region of an asynchronous network tomeasure/compute timing information for one or more network components(e.g., transceivers) relative to a high quality timing reference signal.For example, a mobile device or an LMU may determine the observed timedifference between frame timing of transceiver signals, and the observedtime difference may be sent to the transceiver or a radio networkcontroller of the communication network to determine the location of themobile device. The location of the mobile device may also be determinedbased on the observed time difference and assistance data (e.g.,position of the reference and neighbor transceivers) received from thecommunication network.

Another location determination solution may include computing anuplink-time difference of arrival (U-TDOA) based on network measurementsof the time of arrival of a known signal sent from the mobile device andreceived at multiple (e.g., four or more) LMUs. For example, LMUs may bepositioned in the geographic vicinity of the mobile device to accuratelymeasure the time of arrival of known signal bursts, and the location ofthe mobile device may be determined using hyperbolic trilateration basedon the known geographical coordinates of the LMUs and the measuredtime-of-arrival values.

As discussed above, conventional location determination solutions aretypically based on single-carrier signals. The various embodimentsinclude a ground-based location determination solution based onmulti-carrier signals. A location determination solution based onmulti-carrier signals may improve the accuracy of the computed locationinformation by, for example, improving the accuracy of the timingestimation (e.g., by expanding the bandwidth of cellular signals).Location determination solutions based on multiple carriers may be usedin both the device-centric (e.g., mobile device-based) andnetwork-centric (e.g., base station-based) approaches, and may beapplied to both 3GPP and 3GPP2 wireless communication technologies.

In various embodiments, a mobile device may be configured to determineits geospatial location based on information collected from mobiledevice sensors (e.g. gyroscope, accelerometer, magnetometer, pressuresensor, etc.), information received from other mobile devices, andinformation received from network components in a communication system.

FIG. 4A illustrates an example communication system within which thevarious embodiments may be implemented. Generally, the mobile device 102may be configured to send and receive communication signals to and froma network 406, and ultimately the Internet 114, using a variety ofcommunication systems/technologies (e.g., GPRS, UMTS, LTE, cdmaOne,CDMA2000™). In the example illustrated in FIG. 4, long term evolution(LTE) data transmitted from the wireless device 102 is received by aeNodeB (eNB) 404 and sent to a serving gateway (S-GW) 408 located withinthe core network 406. The mobile device 102 or serving gateway 408 mayalso send signaling (control plane) information (e.g., informationpertaining to security, authentication, etc.) to a mobility managemententity (MME) 410.

The MME 410 may request user and subscription information from a homesubscriber server (HSS) 412, perform various administrative tasks (e.g.,user authentication, enforcement of roaming restrictions, etc.), andsend various user and control information to the S-GW 408. The S-GW 408may receive and store the information sent by the MME 410 (e.g.,parameters of the IP bearer service, network internal routinginformation, etc.), generate data packets, and forward the data packetsto a packet data network gateway (P-GW) 416. The P-GW 416 may processand forward the packets to a policy and control enforcement function(PCEF) 414 which receives the packets and requests charging/controlpolicies for the connection from a policy and charging rules function(PCRF) 415. The PCRF 415 provides the PCEF 414 with policy rules that itenforces to control the bandwidth, the quality of service (QoS), and thecharacteristics of the data and services being communicated between thenetwork (e.g., Internet, service network, etc.) and the mobile device102. In an embodiment, the PCEF 414 may be a part of, or performoperations typically associated with, the P-GW 416. Detailed informationabout policy and charging enforcement function operations may be foundin “3rd Generation Partnership Project Technical Specification GroupServices and System Aspects, Policy and Charging Control Architecture,”TS 23.203, the entire contents of which are incorporated herein byreference.

In an embodiment, the network 406 may also include an Evolved ServingMobile Location Center (E-SMLC) 418. Generally, the E-SMLC 418 collectsand maintains tracking information about the mobile device 102. TheE-SMLC 418 may be configured to provide location services via alightweight presentation protocol (LLP), which supports the provision ofapplication services on top of TCP/IP networks. The E-SMLC 418 may sendor receive (e.g., via LPP) almanac and/or assistance data to and fromthe MME 410 and/or eNB 404. The E-SMLC 418 may also forward external ornetwork initiated location service requests to the MME 410.

In addition, the mobile device 102 may receive information from theserving eNodeB 404 via System Information Blocks that includes theneighbor cells to scan that are on the same system using the samefrequencies or different frequencies, Home eNB (HeNB), in addition toCDMA, GERAN and UTRA cells.

FIG. 4B illustrates logical components, communication links, andinformation flows in an embodiment communication system 450 suitable foruse in determining the location of the mobile device. The communicationsystem 450 may include a network location based system 452, a corenetwork 454, and a radio access network 456. The communication system450 may also include an application module 458, a position calculationmodule 460, a wireless grouping module 462, and a sensor data module464, any or all of which may be included in a mobile device 102. Theapplication module 458 (e.g., client software) may request and receivelocation information from the network location based system 452 (e.g.,through the core network 454 and the radio access network 456).Likewise, the network location based system 452 (or another clientattached to, or within, the core network 454) may request and receivelocation information from the application module 458.

In various embodiments, the mobile device 102 may be configured todetermine its geospatial location based on information collected frommobile device sensors (e.g. gyroscope, accelerometer, magnetometer,pressure sensor, etc.), information received from other mobile devices,and information received from network components in a communicationsystem. In an embodiment, the collection and reporting of sensorinformation may be controlled/performed by the sensor data module 464.For example, the application module 458 may retrieve/receive sensorinformation from the sensor data module 464 and send the sensorinformation to the position calculation module 460 to compute thelocation of the mobile device locally for position updates and/orposition augmentation. The application module 458 may also send thecomputed location information to the network location based system 452and or other mobile devices.

As mentioned above, in various embodiments, the mobile device 102 may beconfigured to determine its geospatial location based on informationcollected from other mobile devices. In these embodiments, two or moremobile devices may be organized into groups. Each mobile device may alsoshare its location information with the other mobile devices with whichthe mobile device is grouped. For example, mobile devices may beconfigured to share their current location and/or position information(e.g., latitude, longitude, altitude, velocity, etc.) and an estimate ofa distance between themselves and a target mobile device with othermobile devices in their group.

In an embodiment, the grouping of mobile devices may be controlled bythe wireless grouping module 462. For example, the application module458 may retrieve wireless group information (e.g., informationpertaining to the locations of other mobile devices) from the wirelessgrouping module 462, and send the group information to the positioncalculation module 460 to perform local calculations for positionupdates and/or position augmentation. In an embodiment, the positioncalculation module 460 may perform the local calculations based on bothsensor information received from the sensor data module 464 and groupinformation received from the wireless grouping module 462.

In an embodiment, the mobile device 102 may be configured toautomatically share its location information with other mobile devicesupon discovery of the other mobile devices. Mobile devices may augmenttheir location information (e.g., position coordinates) with informationreceived from other mobile devices within same geographic location, andin a controlled pseudo ad-hoc environment. Since the shared locationinformation (e.g., latitude, longitude, altitude, velocity, etc.)involves a relatively small amount of data, in an embodiment the mobiledevices may receive such information from a network server by in-bandand or out-of-band signaling.

When implemented in a 3GPP-LTE network, the various embodiments mayinclude an E-SMLC 418 component configured to send and receive locationinformation (e.g., latitude, longitude, altitude, velocity, etc.) to andfrom the mobile devices, which may be achieved both on-net and off-net.The location information may be delivered in standard formats, such asthose for cell-based or geographical co-ordinates, together with theestimated errors (uncertainty) of the location, position, altitude, andvelocity of a mobile device and, if available, the positioning method(or the list of the methods) used to obtain the position estimate

To aid in the determination of the locations of mobile devices, 3GPP-LTEnetworks have standardized several reference signals. Variousembodiments may use these reference signals for timing based locationand positioning solutions. Such reference signals may include theprimary and secondary synchronization signals and the cell specificreference signals.

As mentioned above, two or more mobile devices may be organized intogroups. Mobile devices within the same group may be part of the samenetwork, or may be associated with different networks and/or networktechnologies. The mobile devices within the same group may also operateon different network operating systems (NOSs) and/or radio accessnetworks (RANs).

FIGS. 5A-5C illustrate functional components, communication links, andinformation flows in an embodiment method of grouping mobile devices andsharing location information between grouped mobile devices. Withreference to FIG. 5A, after a mobile device 102 is powered on, themobile device 102 may scan the airwaves for predefined and/or preferredradio frequency carriers and/or systems with which the mobile device 102may connect to the network. If the mobile device 102 does not find anappropriate network with which it may connect (or loses its connection)the mobile device 102 may scan the airwaves for other radio accesssystems (e.g., mobile network, radio access point associated with amobile device, etc.) to acquire (i.e., connect to) until a connection toa network/Internet 510 is established. These operations may also beperformed in the event of a dropped call or power interruption.

The mobile device 102 may also begin acquiring GPS signals whilescanning the airwaves for radio frequency carriers and/or systems. Ifthe mobile device 102 cannot acquire GPS signals, a network component(not illustrated) may help determine the relative position of the mobiledevice 102 based on one or more of the location determination solutionsdiscussed herein (e.g., based on the antenna used for the radio accesspoint, the time delay, angle of arrival, etc.).

The mobile device 102 may acquire (i.e., connect to) an appropriateradio access system, radio frequency carrier and/or system via themobile device's system acquisition system. In the examples illustratedin FIGS. 5A-5C, the mobile device 102 establishes a connection to anetwork 510 via an eNodeB 404. However, it should be understood that anyor all of the communication technologies discussed above arecontemplated and within the scope of the various embodiments.

After the mobile device 102 acquires the radio access system, thenetwork 510 (i.e., a component in the network such as a server) willknow the approximate location of the mobile device 102 (e.g., via one ormore of the location determination solutions discussed above, such asproximity to base towers). In addition, the mobile device 102 maycompute its current location (e.g., via GPS and/or the locationdetermination solutions discussed above), store the computations in amemory of the mobile device, and report its current location to thenetwork 510.

In addition to knowing the approximate location of the mobile device102, the network 510 may also be informed of the locations of othermobile devices 502 and the proximity of the other mobile devices 502 tothe recently acquired mobile device 102.

FIG. 5B illustrates that the network 510 may send instructions/commandsto the mobile devices 102, 502 to cause the mobile devices 102, 502 togroup with mobile devices 102, 502 and possibly others. In anembodiment, the network 510 may be configured to automatically group themobile devices 102, 502 based on the proximity of the devices 102, 502with respect to one another. In an embodiment, the network 510 may beconfigured to allow an incident command system (ICS) commander to groupthe devices. In an embodiment, the network 510 may be configured toallow the mobile devices to form groups based on their proximity to oneanother. FIG. 5C illustrates that the mobile device 102 may pair/groupwith another mobile device 502 and/or establish communication links sothat the mobile devices 102, 502 may share real-time relative locationinformation with each other. Two or more grouped/paired mobile devices102 and 502 may identify their relative positions to each other bysending relative location information over the established communicationlinks. The relative location information may include time-to-arrival,angle-of-arrival, and existing or self-aware location information. Themobile devices 102, 502 may be configured report sensor information toeach other and/or the network 510. The sensor information may include x,y, z coordinate information and velocity information. The sensorinformation may be polled on a continuous basis, may be requestedperiodically, and/or made available on demand in response tonetwork/system requests.

In an embodiment, a mobile device 102, 502 may be configured to reportsensor information in response to determining that there is a highlikelihood that there has been change in a location of the mobile device102, 502 (e.g., in response to detecting motion). The mobile devices102, 502 may also be configured collect and report sensor information tothe network 510 in response to receiving an instruction/command from thenetwork 510 (i.e., a component in the network such as a server or E-SLMC418 illustrated in FIG. 4). The network 510 (i.e., a component in thenetwork) may be configured receive the sensor and location informationfrom the mobile devices 102, 502, and compute and store informationabout the distances (e.g., in time delay and angle of arrival withrespect to the mobile devices 102, 502).

In an embodiment, the reporting of sensor information may be based onlocal parameter settings. For example, the mobile devices 102, 502 maybe configured to transmit sensor information when any of the measuredparameters (e.g., x, y, z and velocity information) meet or exceed athreshold value (e.g., exceed a rate-of-change, meet a timeout limit),which may be identified by local parameter settings stored in a memoryof the mobile devices 102, 502. In an embodiment, the mobile devices102, 502 may be configured to re-compute and/or update their locationinformation in response to determining that the measured parameters(e.g., x, y, and z coordinates and velocity information) meet or exceeda threshold value.

In an embodiment, a mobile device 102 and/or the network 510 (i.e., acomponent in the network) may be configured to compare collected sensorinformation to computed latitude and longitude coordinates, relativealtitude information, and other available information to determine ifthere is a discrepancy between the collected/measured values and theexpected values. When it is determined that there exists a discrepancybetween the expected and measured values, the mobile device 102 and/ornetwork 510 may perform additional measurements to improve the locationaccuracy of the measurements/location information.

FIG. 5D illustrates an embodiment mobile device method 550 for groupingmobile devices and sharing location information between grouped mobiledevices and the network to compute enhanced location information. Aftera mobile device is powered on, in block 552, the mobile device may scanthe airwaves for predefined and/or preferred radio frequency carriersand/or systems with which the mobile device may connect. In block 554,the mobile device may begin acquiring GPS signals while scanning theairwaves for radio frequency carriers and/or systems. If the mobiledevice cannot acquire GPS signals, the mobile device or a networkcomponent may, as part of block 554, determine the relative position ofthe mobile device based on one or more of the location determinationsolutions discussed herein. In block 556, the mobile device may acquire(i.e., connect to) an appropriate radio access system, radio frequencycarrier, system and/or network.

In block 558, the mobile device may compute its current location (e.g.,via GPS and/or the location determination solutions discussed above),store the computations in a memory, and report its current location tothe network. In block 560, the mobile device may group with other mobiledevices in response to receiving instructions/commands from a networkcomponent and/or in response to detecting that the other mobile devicesare within a predefined proximity to the mobile device (i.e., within athreshold distance). In block 562, the mobile device may share itscurrent location information, as well as information collected fromsensors, with the grouped mobile devices. In block 564, the mobiledevice may receive location and/or sensor information from the groupedmobile devices. The sensor information may include x, y, z coordinateinformation, bearing, and velocity information.

In block 566, the mobile device may identify the relative positions ofthe other mobile devices, which may be achieve by evaluating thelocation and sensor information received from the other mobile devicesand/or via any or all of the location determination solutions discussedherein. In block 568, the mobile device may send the relative locationinformation, its current location information, and/or sensor informationto a network component and/or the other mobile devices, which mayreceive the sensor and location information and compute updated locationinformation (e.g., based on distance in time delay and angle of arrival,relative altitude information, etc.). In block 570, the mobile devicemay receive updated location information from the network componentand/or the other grouped mobile devices. In block 572, the mobile devicemay update its current location calculation and/or information based onthe information received from the network component and/or the othergrouped mobile devices. The operations of blocks 562-572 may be repeateduntil the desired level of precision is achieved for the locationinformation.

FIGS. 6A-6D illustrate functional components, communication links, andinformation flows in an embodiment method for computing locationinformation in which the grouped/paired mobile devices 102, 502 areupdated with their respective location information.

FIG. 6A illustrates that the mobile device 102 may communicate with aserving eNodeB 404 to relay its location information to the network 510and/or to receive location information from the network 510.

FIG. 6B illustrates that another mobile device 502 may also communicatewith the serving eNodeB 404 to relay its location information to thenetwork 510 and/or to receive location information from the network 510.

FIG. 6C illustrates that the grouped/paired mobile devices 102, 502 maycommunicate with each other to determine the distance between eachother, which may be achieved by the mobile devices 102, 502communicating various types of information, such as time-of-arrival,relative position with angle-of-arrival measurements, and other similarvalues, measurements, or computations. The mobile devices 102, 502 maythen re-compute, refine, and/or update their current locationcalculations and/or location information based on information receivedfrom the other mobile devices 102, 502.

FIG. 6D illustrates that the grouped/paired mobile devices 102 and 502may send their self-aware location information and/or relative locationinformation to the network 510 (via the serving eNodeB 404), and receiveupdated location information from the network 510. For example, themobile devices 102 and 502 may send their present location coordinates,distances between mobile device (e.g., distance to each other),altitude, and bearings (e.g., where mobile device 102 is with respect tomobile device 502) to the network 220. The network may compute updatedlocation information based on the received information (e.g.,coordinates, sensor information, proximity information, etc.), and sendthe updated location information to the mobile devices 102, 502. Themobile devices 102, 502 may then re-compute, refine, and/or update theircurrent location calculations and/or location information based oninformation received from the network.

The operations discussed above with respect to FIGS. 6A-6D may berepeated so that the mobile devices 102, 502 recursively, continuously,and/or periodically re-compute, refine, and/or update their currentlocation calculations and/or location information based on updatedinformation received from the other mobile devices and/or the network510 until the desired level of precision is achieved for the locationinformation.

FIG. 6E illustrates an embodiment system method 650 of determining thelocation of two or more grouped mobile devices. In block 652, a firstmobile device may send and/or receive current location information toand from a network component. In block 654, a second mobile device maysend and/or receive current location information to and from a networkcomponent. In block 656, the first and second mobile devices maycommunicate with each other to determine the relative distances betweeneach other, which may be achieved by communicating various types ofinformation, including time-of-arrival, relative position withangle-of-arrival measurements, velocity, altitude, etc.

In block 658, the first and/or second mobile devices may re-compute,refine, and/or update their current location calculations and/orlocation information based on information received from the other mobiledevices and/or the network. In block 660, the first and/or second mobiledevices may send their updated current location calculations and/orlocation information to the network component, which may receive thecalculations/information and compute updated location information (e.g.,based on distance in time delay and angle of arrival, relative altitudeinformation, etc.). In block 662, the first and/or second mobile devicesmay receive updated location information from the network. Theoperations in blocks 658-662 may be repeated until the desired level ofprecision is achieved for the location information.

It should be understood that the methods and operations discussed abovewith reference to FIGS. 5A-5D and 6A-6F may also be performed such thatthey include more than two devices. For example, in an embodiment, themobile devices may be grouped into units of four (4) such that eachmobile device may triangulate its position relative to the other mobiledevices in the same group.

In an embodiment, a mobile device 102 and/or a network component maystore relative location information for all the mobile devices withineach group, based on the type of grouping. For example, a networkcomponent may store relative location information for all the mobiledevices grouped/paired by an incident command system (ICS) commander.Likewise, the network component may store relative location informationfor all the mobile devices grouped/paired based on their proximity toeach another.

In an embodiment, the mobile device 102 may be configured to detect alow battery condition, and initiate operations to conserve battery. Forexample, a mobile device 102 may be configured to turn off its radioand/or terminate or reduce its participation in the group/pairinginformation exchange. As another example, a mobile device 102 may beflagged or identified as having a low battery condition, and the othergrouped/paired mobiles devices may be informed of the low batterysituation so that update intervals may be adjusted to reduce batteryconsumption.

FIG. 6F illustrates an embodiment method 670 of adjusting the updateintervals in a mobile device in response to detecting a low batterycondition. In block 672, the mobile device may detect/determine that theamount of power remaining in the mobile device battery is below apredetermined threshold. In block 674, the mobile device may transmit asignal or otherwise inform grouped mobile devices of the detected lowbattery condition. In block 676, may initiate operations to conversepower, such as by turn off its radio and/or reducing its participationin exchanging information with grouped mobile devices. In block 678, themobile device and/or the informed grouped mobile devices may adjust theupdate intervals with respect to the mobile device to reduce the load onthe mobile device.

As discussed above, grouped mobile devices may share various types ofinformation to improve the accuracy of the location determinationcalculations. For the information shared between grouped/paired mobiledevices, a comparison may be made for the path, range, between themobile devices using any or all of the information available to themobile devices (e.g., location coordinates, sensor information,proximity information, etc.). If the two mobile devices report relativepositional information that is within a user or network defined rangetolerance as being acceptable this is information may be forwarded tothe network. If the relative positional information is not within theuser or network defined range tolerance, additional polling operationsmay be performed to improve the accuracy of the measurements or locationinformation. The above-mentioned operations may be repeated until thedesired level of accuracy is achieved. In an embodiment, the number oftimes the above-mentioned operations are repeated may determined basedon a user-definable values which can be set by the network, user oralgorithm used.

As mentioned above, a mobile device 102 may include two or more of thesame type of sensor. In the embodiments in which the mobile device 102includes more than one of the same type of sensor (e.g., includes twoaccelerometers), one of the sensors (e.g., one the two accelerometers)may be identified as a master sensor. The values measures by each sensormay be compared, and if the difference between the values falls within atolerance range, the values measured by the master sensor may be used tocompute the sensor parameters (e.g., x,y,z and velocity parameters). Ifthe difference between the values falls outside a tolerance range, themobile device may use information collected from other sensors (of thesame or different types) to determine if the values measured by themaster sensor are consistent with expected values. For example, themobile device may use information collected from various other types ofsensors to compute sensor parameters (e.g., x,y,z and velocityparameters), and compare the computed sensor parameters to similarsensor parameters computed based on the values measured on the mastersensor to determine if the master sensor is functioning correctly.Values measured on the master sensor may also be compared to informationstored in the network or other mobile devices to determine if the mastersensor is functioning correctly. If it is determined that the mastersensor is not functioning correctly, a secondary sensor may bedesignated as the master sensor. The previous master sensor may bedemoted to standby status (i.e., for use if the primary sensor has afailure) and not used for immediate positional calculations.

As mobile devices move into an area, the mobile devices may be asked togroup/pair with more devices. The number devices that a mobile devicecan group/pair with may be restricted by user configuration, through thesystem, and/or user intervention so as to conserve battery andcomputational efforts (e.g., when the mobile device detects a lowbattery condition).

In an embodiment, proximity grouping may be used in the x, y and zcoordinates/fields and/or for velocity and acceleration information.

In the event that a mobile device is unable to group with another mobiledevice with which it is instructed to group/pair with (e.g., due to a RFpath problems), the mobile device may group with yet another mobiledevice in an ad-hoc fashion. If no mobile device is pairable with themobile device, it may rely on its own geographic and/or and sensorinformation to report to the network.

When a mobile device 102 is undetected as being within a given proximityof a grouping radius, other mobile devices in the same group as themobile device 102 may be informed of the decision to degroup/depair themfrom the mobile device 102. In an embodiment, the system may beconfigured so that an approval from the incident commander or user isrequired before the mobile is degrouped/depaired. In an embodiment, thismay be achieved may transmitting a signal to a mobile device of theincident commander or user requesting approval, to which the incidentcommander or user may send a reply approving or disapproving of therequest to degroup/depair. In an embodiment, the degrouping/depairingprocess may be transparent to the mobile device users.

In the event that a mobile device is unable to communicate with thenetwork, the mobile device may send telemetry information pertaining tolocation services (and other telemetry information) to a grouped mobiledevice for relaying to the network.

In an embodiment, polling for information may be performed once thenetwork has lost communication with the mobile device. Mobile devicesthat and known to be grouped to the mobile device may be instructed tocommunicate with the disconnected mobile even when it is trying toreacquire the network. A logical sequence based on proximity, signalquality to the network, and/or battery strength may be used to determinewhich mobile device will be used as a relay for communicating with thenetwork.

The relayed telemetry information may include more than just positionalinformation. For example, the telemetry information may also include biosensor and user bio information reporting on the environment and userconditions, including heart rate and temperature, CO, O2 and othersensor information.

In an embodiment, the network may continuously measure/monitor theconnected mobile devices. Knowing their location and relative locationto each of the other mobile devices enables the network to continuouslymeasure the uplink and downlink communication paths. If a communicationpath degradation occurs and begins to fall within a defined systemquality range (which may be user defined), a mobile device may beinstructed to either handover to another radio access node for the samenetwork and/or network technology, or be instructed to initiate toperform relay operations to relay communications though a defined mobiledevice as a secondary signal path.

In the event that a communication link is lost with the network themobile device may attempt to acquire itself on another network. Whilethe acquisition process is underway, a mobile device may act as a meshdevice. Other mobile devices in the proximity group may also connect asa mesh network.

In an embodiment, the mobile devices may utilize dead reckoningtechniques to compute location information. Mobile devices may store theinformation for use in calculating more accurate location information,and may eventually relay to another mobile device which has networkaccess or until one of the mobile devices or both devices have access tothe initial network or another network and granted access to whether itis public or a private network.

FIG. 7 illustrates normal operating conditions in which a mobile device102 will periodically scan for other cells 704, including its servingcell 903. If the radio access points are part of the network then themobile device will report the identity and signaling informationrequired by the existing network to determine (e.g., via triangulatingand/or trilateration) the mobile device's location based on a networkapproach. If the mobile device detects a radio access point is not partof its preferred cell selection process, it may attempt to read thecoordinates and positional information from the access point that isbroadcast.

Once synched with the access point the mobile device may determine thetiming difference and other requisite information to help determine itsrelative location and distance from the access point. This informationmay be related to the location system used by the mobile device to helprefine its current location calculations.

Additionally the mobile device may be configured to compare each cellread to its own coordinate and using bearing and time difference for allthe cells it reads. The mobile device may then triangulate on its ownposition.

During a 911 call a software application on the distressed mobile devicemay be executed. The software application may access an active neighborlist, read the overhead of each cell, and use that information totriangulate on the mobile device's own positions. The mobile device mayalso read the time offset for each of the cells.

In this case the system begins to try and locate the distressed mobilesposition with more precision an accuracy to assist First Responders withtriangulating on the distressed mobiles position and sending theinformation to the incident commander and/or public service answeringpoint (PSAP) with a relative distance to target indication that isupdated on pre-defined intervals. If the mobile device has lost contactwith the 911 center, PSAP then the last location is continuously displayand any velocity information is also relayed to assist the firstresponders.

In an emergency, the mobile device 102 may be configured to send itslocation information to the network. The mobile device 102 may beconfigured to automatically send its location information in response todetecting the emergency, or may provide the user with an option to sendthe location information. In an embodiment, the mobile device 102 may beconfigured to send its location information in response to a networkinitiated command.

Each mobile device may become an access point (AP). The decision to bethe access point may be periodically updated while still incommunication with the network, or when no network is found. Uponpowering up, each mobile device may act as a client, and on a pseudorandom time interval, the mobile devices may become an access point andthen a client.

The location based methodology may be the same for a frequency-divisionduplexing (FDD) and a time-division duplexing (TDD) system. However inthe event that the communication link between the mobile device and thenetwork is lost, the mobile device may be configured to relay itstelemetry information through another mobile device having networkaccess.

In an embodiment, all information sent via wireless communication linksmay be digital. In an embodiment, the information may be encrypted to arequisite advanced encryption standard (AES) standards level or theappropriate encryption level needed for the requisite communicationsystem and access method used.

Generally, the location based systems (LBS) may utilize reactive orproactive based methods. In a reactive location based system, the mobiledevices may synchronously interact with each other on a time basis orsome other predetermined update method. In a proactive location basedsystem, the mobile devices may update their location information basedon a set of predetermined event conditions using an algorithm. Thevarious embodiments may include both reactive and proactive aspects,taking the best of both approaches to enhance location accuracy andprecision.

Various embodiments may include location determination solutions thatutilize horizontal data (i.e., a set of reference points on the Earth'ssurface against which position measurements are made) and/or verticaldata. Horizontal data define the origin and orientation of thecoordinate system and are prerequisites for referring a positionrelative to the Earth's surface. Vertical data are based on geoids,which primarily serves as a basis to determine the height of a positionrelative to means sea level for which the geoids act as a benchmark fororigin and orientation. Various embodiments may utilize horizontal andvertical data to provide/generate enhanced three dimensional locationinformation. The horizontal and vertical data can be global, national,local or custom depending on the locality and positioning referencesystem utilized.

Traditionally global data are used for position location as compared toa local datum. Global data are used for initial position fixing ifpossible and are based on GPS coordinates. Local data are based on aparticular position on the surface of the earth, which allows for a nonGPS based location based services to take place. The various embodimentsmay use global data, local data, or both. In an embodiment, GPS may beused to help identify the initial positional fix, and may be augmentedby dead reckoning and a hybrid trilateration solution that utilizes bothnetwork and terminal based positioning. In this embodiment, both localand global data may be used. If GPS determined position information isunavailable then the initial position may be sent to the same positionas that of the reporting mobile or a distance that is estimated usingreceived signal strength indication (“RSSI”) and/or time of flight suchthat 0.5 of the estimated distance is applied to the horizontalcomponent and vertical component of the reporting mobile device and thealtitude, which may also be reported by the additional mobile devices.

Generally, a hybrid lateration and trilateration solution includes amobile device performing a measurement and sending it to the network,and a network component performing the location determinationcalculations. The various embodiments include a hybrid lateration andtrilateration solution in which the mobile device performs the locationdetermination calculations, with and without the support of the networkcomponents.

Various embodiments may include sensor fusion operations in which acollaborative approach is used so that the sensors do not act asindividual sensors, but as a collective team. As discussed above, themobile device may include various sensors (e.g., accelerometer, gyros,magnetic compass, altimeters, odometers, etc.) capable of generatingheading, orientation, distance traveled, and velocity as part of thesensor information collected on the mobile device. In variousembodiments, information collected from any or all the internal sensorsmay be used for improving location or positioning accuracy and/orconfidence improvements. Various embodiments may compute locationinformation based on information from multiple sensors, with or withoutthe aid of radio frequency propagation information.

The sensor fusion operations may include the sharing of telemetryincluding sensor data indicating relative movement of the individualmobile device, which enables temporal readings to assist in the locationestimate, either with external assistance or dead reckoning.

FIG. 8 illustrates an embodiment mobile device method 800 fordetermining the location of a mobile device in a wireless network. Inblock 802, a mobile device may determine its current location using anyof the above mentioned location determination solutions to produce afinal location estimate. In block 804, the mobile device may share itslocation information (i.e., the final location estimate) with othergrouped mobile devices and/or receive location information from othergrouped mobile devices. In block 806, the mobile device may compute andsend a final location estimate, updated distance vector and sensorinformation to a network component for improved positional fix. In block808, the mobile device may receive updated location information from thenetwork component, and perform its own positional fix based on mobiledata information received from the network. In block 810, the mobiledevice may update its location information and/or confirm its locationinformation using dead reckoning to enhance positional accuracy.

Dead reckoning may provide the needed positional corrections as a localdatum method for positioning when GPS or other network relatedpositioning solutions are not available. Additionally dead reckoning mayenhance the location position accuracy and precision calculations byproviding and additional horizontal and vertical datum comparisons.

With dead reckoning, the current position may be deduced (orextrapolated) from the last known position. The dead reckoning accuracyrequires a known starting point which either can be provided by thenetwork, GPS, near field communication link, RF beacon, a predeterminedzero position, or via another mobile device. For example, if GPS initialposition information is available then the initial position may be setto zero or a distance that is estimated using RSSI or time of flightbetween another mobile device such that 0.5 of the estimated distancebetween the mobile device and a measurement location (e.g., anothermobile device) is applied to the horizontal component and verticalcomponent of the reporting mobile device and the altitude, which may bereported by the additional mobile device

A dead reckoning system may be dependent upon the accuracy of measureddistance and heading, and the accuracy of the known origin. However theproblem with relying on dead reckoning alone to assist in positionalimprovement is error accumulation caused by sensor drift (i.e.,differences or errors in values computed/collected from one or moresensors). In particular, magnetic, accelerometers and gyroscopes aresusceptible to sensor drift. The error accumulation for any of thesensors may increase over undulating terrain, as compared to flatterrain. Bias error and step size error are leading contributors to deadreckoning errors.

Various embodiments may tightly couple the mobile device sensors andcontinuously recalibrate the sensors to reduce any drift problems causedby unaided dead reckoning Additionally, as part of the tightly couplingthe sensors, any bias drift associated with the sensors (e.g., agyroscope) may be address by utilizing a kalman filter to reduce theerrors from the primary and/or secondary sensors (e.g., gyroscopes).

In various embodiments, the mobile device may be configured to includevelocity computations as part of the location determination computationsto account for position changes that occur. When a GPS signal isavailable, the step size (via velocity computation) and compass biaserrors may be estimated by an Enhanced Kalman Filter (EKF). Additionallyif GPS is available, the compass may also be able to identify slowmotion changes due to changes in magnetic inclination. The compass maybe relied upon for motion computations in addition to that ofaccelerometers and gyroscopes, with and without the availability of GPS.

Dead reckoning accuracy degrades with time, requiring regular positionupdates or positional corrections. Therefore, the mobile device may beconfigured to not only use its own internal sensors to compute thelocation/positional information, but may also communicate with othermobile devices to leverage their location/positional information toenhance its own location/positional information. In essence, the mobiledevices may act as RF base stations, proving the lateration capabilityto improve the positional accuracy of other mobile devices.

In an embodiment, a mobile device may be configured to poll one or moreother mobile devices to gain a better positional fix on its location.

Mobile devices may be grouped together, either through assignment by thenetwork or through the mobile device acquiring/detecting/connecting toother mobile devices (which may or may not be in the same network) aspart of a discovery method for sharing location information.

Location information may be shared via the use of a near fieldcommunications system (e.g., Bluetooth®, ultrawideband, peanut radios,etc.), infrared, ultrasonic, and other similar technologies, such as viathe use of WiFi. The wireless communications may also be ad hoc orinfrastructure based, or based on a TDD system, such as LTE, SD-CDMA,TD-CDMA, or any other TDD methods.

In an embodiment, the mobile device may be configured to initiate thesharing of location/position information in response to receiving anetwork-driven grouping request from a network component.

In an embodiment, when the mobile device has lost contact with thenetwork, it may attempt to find a suitable mobile device to help in itslocation determination computations, and for possible connection to thenetwork (e.g., via a relay).

In an embodiment, the mobile device may be configured to send a requestfor location information to another mobile device. The request may besent after the authentication process between mobile devices, and mayinclude a time stamp which may be sub-seconds in size (milliseconds).Another mobile device may respond with a message that also has its timestamp and when it received the time stamp from the initiating mobiledevice.

Several messages (e.g., three messages) may be exchanged quickly betweenthe mobile devices to establish time synchronization and sharelocation/positional information that includes horizontal, vertical, andaltitude coordinates (e.g. x, y, and z coordinates), a velocity, andacceleration component in each message. The time differences along withthe x, y, and z coordinates may be compared with possible pulses orpings to establish an estimated distance vector between the devices.

When the distance vector and the x, y, z coordinates of two mobiledevices are known, a point-to-point fix may be established. This processmay be repeated for all the mobile devices in a group that has beenassigned or created by the mobile device itself. Having multipledistance vectors from other points to the mobile will enhance thepositioning accuracy.

A mobile device may be configured to report back to the network locationserver the distance vectors it has found between different mobiles. Theother mobile devices also involved with the positioning enhancement mayalso report their distance vectors to the network to have their overallposition accuracy improved as well.

The positional accuracy is meant to be done in incremental steps and theprocess will continue until no more positional improvements will beachievable. The positional accuracy improvement threshold may beoperator defined, and may be stored in a mobile device memory.

When collecting the distance vectors and other positional information,if the error in position is greater than x % for a lower positionalconfidence level then no update may be required. As the mobile devicereceives other sensor data and more than a pre-described distance in anydirection or a combined distance vector than the positional updateprocess begins again. However if the x % of positional confidence levelis less than desired additional positional, updates may be made with themobile devices grouped together in an interactive process to improve theconfidence level of the positional information.

It is important to note that typical positional location methods thatare used currently by the network are not necessarily replaced withabove-described positional lateration. Instead, the hybrid laterationmethod may be used in various embodiments to augment the positioningaccuracy and confidence for network based position request due toboundary changes or paging requests or other position location triggeredevents.

FIGS. 9A-9E illustrate various logical components, information flows anddata suitable for use in various embodiments. FIG. 9A illustrates thatmobile devices 901, 902, 903, and 904 are communicating with thewireless network via multiple cell sites/radio access points/eNodeBs911. The mobile devices 901, 902, 903, and 904 may compute a relativefix on their initial location using any of the location determinationsolutions discussed above. A first mobile device 901 may be instructedto find and communicate with the other mobile devices 902, 903 and 904,and/or any or all of mobile devices 902, 903 and 904 may be instructedto communicate with the first mobile device 901. The mobile devices 901,902, 903, and 904 may be grouped together (e.g., via one of the groupingmethods discussed above). The network may also designate one of themobile devices 901 (e.g., a mobile device having a high positionconfidence) to be used as the reference or beacon for the other mobiledevices 902, 903, and 904 within the group of mobile devices 901, 902,903, and 904.

FIG. 9B illustrates that a combination of circular and hyperbolictrilateration operations may be performed as part of an embodimentlocation determination solution. For example, if any of the coordinatedata provided by the sensors and/or mobile devices is in latitude andlongitudinal coordinates, it may be converted to Cartesian coordinatesto facilitate a hybrid lateration calculation. In the exampleillustrated in FIG. 9B, the mobile devices 901 has been designated asreference mobile device, reference number 912 identifies the position tobe determined/computed (i.e., with a high level of accuracy) withrespect to mobile device 901, reference number 910 identifies a threedimensional sphere that encompass the mobile device 901, and referencenumber 914 identifies an area of the three dimensional sphere (with x, yand z coordinates) within which the device exists.

FIG. 9C-9D illustrate that distance vectors may be computed between themobile devices 901, 902, 903, and 904 as part of an embodiment locationdetermination solution. In FIG. 9C mobile 901 using the hybridtrilateration method determines is relative position with respect tomobile devices 902, 903 and 904 respectively, Additionally, referencenumbers 915, 909, and 916 identify the relative areas of mobile devices902, 903, and 904, respectively. As part of the hybrid trilaterationoperations of the embodiment location determination solution, mobiledevices 902, 903, and 904 may locate mobile device 901, and the mobiledevice 901 may compute a distance vector between itself and mobiledevices 902, 903 and or 904. The mobile device 901 may initiatecommunications with mobile device 902 (although mobile device 902 couldinitiate the communication) and exchange time stamps, positionalinformation, sensor data. The same process may occur with respect tomobile devices 904 and 903, in which positional and sensor informationis exchanged.

As illustrated in FIG. 9D, the mobile devices 902, 903, and 904 mayestablish a distance vector between themselves and mobile device 901.The same process may occur with respect to mobile devices 902, 903and/or 904, in which positional and sensor information is exchanged.Where mobile device 902 undergoes the same process as that done withmobile device 901 as part of the hybrid trilateration process, mobiledevice 901 may use mobiles 902,903, 904 to enhance it positionalinformation and mobile device 902 may use mobiles 901,903 and 904 toenhance its positional information, and so forth for all the mobiledevices that are grouped together.

The three circles or ellipses 909, 915 and 916 illustrated in FIG. 9Cand the three circles or ellipses 906, 907 and 908 illustrated in FIG.9D do not intersect at a given point, but span an area of a particularsize depending on the range involved.

FIG. 9E illustrates an embodiment hybrid trilateration method in whichthe position of mobile device 901 is validated or improved upon. As partof the hybrid lateration method, separate calculation operations may berequired for each set of x, y and z coordinates, in addition toaccounting for velocity and acceleration. However, the ability to havethree mobile devices 902, 903, and 904 locate mobile device 901 maypresent an error window (or an error area) for each coordinate planerepresented by reference number 930. The error window/area may be acombination of range errors from the mobile devices 902, 903, and 904.Contributing to the error window/area is the hybrid range errorsillustrated by reference numbers 921, 922 and 923, where: referencenumber 921 is the hybrid range error associated with mobile device 902;reference number 922 is the hybrid range error associated with mobiledevice 903; and reference number 923 is the hybrid range errorassociated with mobile device 904. Additionally this process can be donewith less or more mobile devices than used in the above example.

For each axis (x, y, or z), a similar process occurs where the errorarea 930 is a combination of determining the range between the othermobile devices and mobile device 901. The hyperbolic lateration is atypical calculation method used in location based systems and is basedon the principal that the range between two locations is the same.However the range determined for the points may not be constant sinceboth can be moving toward, away or together at a similar velocity andtrajectory.

With the hybrid lateration method proposed a corrective distance vectorΔx,Δy,Δz is used that can be used to apply to the estimated position.

The three circles or ellipses 909, 915 and 916 illustrated in FIG. 9Cand the three circles or ellipses 906, 907 and 908 illustrated in FIG.9D do not intersect at a given point, but span an area of a particularsize depending on the range involved. Therefore range is “r” and isdenoted by the subscript representing the distance vector involved.Thus:

r=p _(i)+error

The pseudo range p_(i) deviated from the actual range in any axis due tothe inaccuracy in synchronization or propagation in a multipathenvironment or due to sensor induced errors. Where the distance vectoraccounting for change in direction is:

r _(i)=√(X _(i) −x)²+(Y _(i) −y)²+(Z _(i) −z)²

Three range calculations are then averaged to determine the distancevector that is used. If the previous range calculation r_(j) as comparedto that of the current calculation has an error in excess of a userdefined % or variant then the new measurement is disregarded. Includedwith the distance vector validation may be the fusion sensor informationwhere expected position verse calculated may be included for theconfidence interval.

Range difference=d _(ij) =r _(i) −r _(j)

An iterative process may be used for position improvement, which mayinclude the use of a least squares calculation fit to approximate theposition solution in a step wise basis. The process may continue untilthe range difference measured does not produce any noticeable accuracyimprovement, which may be user-defined, either at the mobile device ornetwork or both.

The multi-lateration calculations may include estimating a location of amobile device based upon estimated distances to three or moremeasurement locations (i.e., locations of three other mobile devices orwireless transceivers). In these calculations, the estimated distancefrom a measurement location (location of another mobile device) to themobile device may be derived from the measured signal strength. Sincesignal strength roughly decreases as the inverse square of theseparation distance, and the transmission power of the mobile device canbe presumed, the distance d_(i) can be simply calculated as:

d _(i)=√(S ₀ /Si _(i))

where:a. d_(i) is the estimated separation distance between a measurementlocation and the mobile device;b. S_(i) is the measured signal strength; andc. S₀ is the strength of the signal transmitted by the other mobiledevice).

Alternatively, the signal strength readings may be translated intodistances using a path loss model, such as the following:

RSSI _(i) =a−cb log₁₀(d _(i))

where:d. a is the signal strength at d_(i)=1 meter;e. b is the path loss exponent; andf. c is the pathloss slope with 20 being used for free space.

The lateration operations may include performing a least squarescomputation, which may accomplished by a processor calculating thefollowing formula:

min_((x,y))Σ(d _(i) −∥MS _(i)−(x,y)∥)²

where:g. d_(i) is the distance calculated based on a measured signal strengthvalue;h. MS_(i) corresponds to the known location/position of the mobiledevice; andi. the minimization value of (x, y) is the estimated position of othermobile devices.

In various embodiments, the velocity and acceleration of the mobiledevice with respect to the three or more reference locations (i.e.,locations of three other mobile devices or wireless transceivers) may bedetermined along with the estimated distance from each referencelocation to the mobile device. The estimated distances to three or moremeasurement locations (i.e., locations of three other mobile devices orwireless transceivers), velocities, and acceleration calculations mayhave their components separated into a horizontal component set, avertical component set, and an altitude component set respectively. Aswill be discussed in greater detail below, each of the component setsmay contain the distance component, velocity component, and accelerationcomponent for each of the reference locations. For example, an “x”component set may contain the distance x components, velocity xcomponents, and acceleration x components associated with all referencelocations. Some embodiments may include executing a kalman filteringprocedure on the component sets individually to produce an estimatedposition of the mobile device.

FIG. 10 illustrates an embodiment hybrid lateration method 100 in whichmobile devices may gain access to the network. The mobile devices may beinstructed to be grouped by the network. Mobile devices 901 and 902 mayinitiate sharing of information for position location, either due to thenetwork driven grouping request or when the mobile device has lostcontact with the network and attempts to find a suitable mobile deviceto help in its position location and possible connection to the networkvia a relay or to another network.

Mobile device 901 may send a request for position information to mobiledevice 902. The information may be sent after the authentication processbetween mobile devices, and may include a time stamp. The time stamp maybe sub seconds in size (e.g., milliseconds). The mobile device 902 mayrespond with a message that also has a time stamp, and timinginformation pertaining to when the mobile device 902 received the timestamp from mobile device 901. Three messages may be transferred quicklyto establish time synchronization. The time differences may then becompared, along with possible pulses or pings, to establish an estimateddistance vector between the mobile devices. Knowing the distance vectorand the x, y, and z coordinates of both 901 and 902, a point-to-pointfix may be established. In various embodiments, the position fix may beextrapolated to synchronize the trilateration time stamp with a timestamp of a dead reckoning calculation. Similarly, the time intervaladopted for dead reckoning calculation updates may be adopted as thetime interval between trilateration recalculations.

The mobile device 901 may then initiate communication with mobiledevices 903, 904 and repeat the operations discussed above with respectto mobile device 902 for each of mobile device 903, 904. After obtainingtwo or more distance vectors along with positional information, themobile device 901 may compare the new coordinates to its previouslycomputed current location, and adjust the location computationsaccordingly.

The positional information distance vectors may be sent to the networkfor positional processing with other network positional information.Based on the position calculated for the mobile device, the network(i.e., a component in the network, such as a network server or E-SMLC)may instruct the mobile device to adjust its positional information.

Additionally the mobile device 901 may also make a positional correctionif the network either does not respond in time, which may result in amessage update time out. Alternatively, when the network cannot make thenecessary correction, and the positional information may used by anothercomponent and/or other mobile devices to perform the necessarycorrections.

If the error is greater than x % for a lower positional confidence levelthen no update is required. As the mobile receives other sensor data andmore than a pre-described distance in any direction or a combineddistance vector than the positional update process begins again. If thex % of positional confidence level is less than desired, additionalpositional updates may be made with the grouped mobile devices (e.g.,iteratively) to improve the confidence level of the positionalinformation. Additionally if the positional information from one of themobile devices that is being attempted to obtain a distance vectorappears to be in error, then that mobile devices data may be selected tonot be used for this iterative step of performing positional updateswith other grouped mobile devices. However it will continue to bequeried as part of the process since its position location could becorrected in one of the steps it is taking to improve its positionlocation as well.

Additionally in the event that one or more mobile devices losecommunication with the core network it will still be possible tomaintain position accuracy through one of the other grouped mobiledevices. In some embodiments, the last position of the mobile device maybe re-used and the amount of error increased. It will also be possibleto continue to maintain a communication link by establishing a networkrelay connection with another of the mobile devices in the same groupwhich still has communication with the network itself.

FIG. 11 illustrates another embodiment hybrid lateration method 100 inwhich a mobile device cannot locate a network due coverage problems. Themobile device 901 may operate in an autonomous mode and attempt tolocate another mobile device. The other mobile device could be used torelay information to the network and possibly set up a near fieldcommunication bridge in addition to providing location enhancementcapability.

In the example illustrated in FIG. 11, mobile device 901 establishes anear field LAN inviting other mobile devices in proximity to communicatewith it. Positional information can then be shared and the mobile device901 can have its location improved and the positional information can berelayed back to the core network via another mobile device.

The mobile device 901 may also communicate its positional informationand establish near field communication link with a mobile device that isnot part of the home network associated with mobile device 901.

The mobile devices may have the USIM, SIM, PRL or access pointinformation pre-built in. The mobile device for first responders mayhave the incident radio system set as their preferred system, or in thecase that the radio access system being used as a public safety network.

For first responders to utilize a wireless mobile network (e.g., LTE)the position location information accuracy needs to improved for inbuilding environments in addition to providing more accurate locationinformation about where the mobile devices are actually located. Whetherthe mobile device is used by a first responder, commercial cellular useror a combination of both.

The positional location improvement for first responders may be helpfulto improve situation awareness, improved telemetry and overallcommunication with the incident commander. Since all incidents for firstresponders tend to be fluid the ability to account for a dynamicenvironment of mobile devices will come into and out of the incidentarea. In addition the mobile devices proximity location to other mobiledevices can and will change as the incident situation changes whereresources are added and or reassigned as the need arises for operationalrequirements.

The use of network and terminal driven position enhancement techniquespreviously discussed may be exploited. The grouping of mobile devicesmay be done either as part of pre-plan, with intervention by theincident commander or driven from the commercial wireless network,public safety wireless network or local incident communication system(ICS) 1204 based on reported proximity of the mobile devices.

FIG. 12A illustrates that upon arriving at the incident scene, a mobiledevice 102 may recognize the existence of a local radio network 1202. Ifthere is no ICS radio network 1204 with which the mobile device mayconnect, the mobile device 102 will continue to communicate via acommercial or other wireless network, 1202.

FIG. 12B illustrates that the mobile device 102 may determine that thereis a valid local radio system 1202 with which it may communicate, andmay have a priority access to small cell system 1204 a based on apreferred network and cell selection process the mobile device 102 hasbeen instructed to use.

FIG. 12C illustrates that the mobile device 102 may transfer theconnection from the local radio system 1202 to the small cell system1204.

For first responders when a situation arises that requires finding a mandown or responding to an emergency call (911) the location based processcan be used to help in the search and rescue of the person.

FIG. 13A illustrates that the mobile device 102 may be identified by thenetwork as being in distress via network monitoring of the mobile device102 or via the mobile device transmitting a distress signal. Thedistressed mobile device 102 may determine that it has lostcommunication with the network, and may instruct the wearer/user toeither disable or initiate a distress signal. The mobile device 102,upon initiation of a distress signal, may begin a grouping processpreviously defined.

FIG. 13B illustrates that the network 510 to which the serving eNodeB404 is connected to may instruct a mobile device 1302 in the same groupas the distressed mobile device 102 to report the last known location ofthe mobile device 102 and time stamp.

FIG. 13C illustrates that the network 510 may instruct additionalmobiles devices 1304 to attempt to group with the distressed mobiledevice 102.

FIG. 14 illustrates that when the mobile device 102 is unable tocommunicate with the network 510, it may been operating under a deadreckoning process and continue to attempt to locate other mobile devices1402, 1404 and group with them under an ad-hoc scheme.

Once the mobile device has been grouped, or is still connected to thenetwork, the relative location of the mobile device will be sent to allthe mobile devices that are in active search for that mobile device. Theselection of which mobile devices will be searched may be determined byoperator intervention and selection.

As discussed above, the various embodiments include methods, and mobiledevices configured to implement the methods, of determining a locationof a mobile device, which may include determining an approximatelocation of the mobile device, grouping the mobile device with awireless transceiver (e.g., a second mobile device, etc.) that is inproximity to the mobile device to form a communication group, sendingthe determined approximate location of the mobile device to the wirelesstransceiver, receiving on the mobile device location information (e.g.,a latitude coordinate, a longitude coordinate, an altitude coordinate,etc.) from the wireless transceiver, and determining a more preciselocation of the mobile device based on the location information receivedfrom the wireless transceiver. In an embodiment, the method may includegrouping the mobile device with a plurality of wireless transceivers inproximity to the mobile device to form the communication group, andreceiving location information from the plurality of wirelesstransceivers in the communication group. In some embodiments, the methodmay also include sending information relating to the determined moreprecise location of the mobile device and the received locationinformation to a server, receiving updated location information from theserver, and re-computing the more precise location of the mobile devicebased on the updated location information (i.e. the information receivedfrom the server).

As also discussed above (e.g., with reference to FIG. 8) a mobile devicemay be configured determine its current location using any of a numberlocation determination solutions to produce a final location estimate,share its location information (i.e., the final location estimate) withother grouped mobile devices and/or receive location information fromother grouped mobile devices, compute and send a final location estimate(and updated distance vector and sensor information) to a networkcomponent for an improved positional fix, receive updated locationinformation from the network component, and perform its own positionalfix based on mobile data information received from the network. Themobile device may then update its location information and/or confirmits location information using dead reckoning to enhance its positionalaccuracy.

Further embodiments include methods, and mobile computing devicesconfigured to implement the methods, of providing an enhanced locationbased services. The mobile computing device may be configured todetermine an initial position, generate at least one set of localposition information based on locally determined location information,receive location information from one or more external location trackingsystems, generate at least one set of external position informationbased on the location information received from the external locationtracking systems, receive distance information from multiple mobiledevices in a communication group, generate proximity positioninformation based on the location information received from the multiplemobile devices in the communication group, and generate a final locationestimation set (a position, velocity, and acceleration value) based onthe local position information, the external position information, theproximity position information and the initial position. The mobilecomputing device may then use the final location estimation set toprovide a location based service (e.g., an emergency location service,commercial location service, internal location service, lawful interceptlocation service, etc.).

FIG. 15 illustrates a method 1500 of determining the location of amobile device via a wireless network in accordance with an embodiment.The operations of method 1500 may be performed by a processor orprocessing core in a mobile device 102. In block 1502, the mobile device102 may receive location information, such as GPS or cell-based locationinformation, from one or more external systems (e.g., an externallocation tracking system, GPS system, a base station, a network server,etc.). In block 1504, the mobile device may determine its initialposition, which may include performing any or all of the above-describedlocation or position determination techniques, algorithms, or methods todetermine or compute an initial position value. For example, the mobiledevice may determine its initial position (or the initial positionvalue) based on GPS coordinates and/or GPS-determined positioninformation received in its GPS circuitry from a GPS system.

The initial position value may be an information structure that includesone or more information fields, component vectors, location information,position information, coordinate information, etc. Similarly, the mobiledevice may include, generate, compute, determine or use a dead reckoningposition estimate value, a combined sensor position estimate value, atrilateration position estimate value, a final location estimate value,and various temporary position and error values, any or all of which maybe information structures that each include one or more informationfields, component vectors, location/position information such ascoordinates, and/or other similar information. In some embodiments, themobile device may include a dead reckoning module that is configured todetermine whether a dead reckoning position estimate value is available,as well as to generate time stamps, use dead reckoning techniques tocompute location information, set the dead reckoning position estimatevalue, and/or perform other similar operations.

In some embodiments, as part of the operations in block 1504, the mobiledevice may determine whether GPS data (e.g., GPS coordinates or GPSdetermined position information) is available in the device. The mobiledevice may also determine, generate, or compute an temporary positionvalue in response to determining that GPS data is not available, and setthe initial position value to the determined temporary position value(e.g., by performing a deep or shallow copy of the temporary positionvalue information structure). In various embodiments, the mobile devicemay determine or compute the temporary position value and/or set theinitial position value to zero (0), to the last known location stored inmemory, or to the RSSI or time of flight with/between another mobiledevice such that 0.5 of the estimated distance is applied to thehorizontal component and vertical component of the reporting mobiledevice. In some embodiments, the mobile device may also derive,determine, or compute an initial altitude value (or generate initialaltitude information) based on information reported by other oradditional mobile devices, and use this initial altitude value tocompute the temporary position value and/or to set the initial positionvalue.

In determination block 1506, the mobile device may determine whether adead reckoning position estimate value is available, which may includedetermining whether the device may utilize one or more dead reckoningtechniques to compute or generate location information for the mobiledevice based on information that is stored in its memory or based oninformation that may be collected from its components (e.g., sensors,etc.). In response to determining that a dead reckoning positionestimate value is not available (i.e., determination block 1506=“No”),the mobile device may wait for a predetermined amount of time (or forthe occurrence of an event, a trigger, notification, collection of data,etc.) and repeat the operations of determination block 1506. Saidanother way, the mobile device may wait until it determines that it hasaccess to sufficient information to use dead reckoningtechniques/methods to compute its current location and set the deadreckoning position estimate value, or until it times out, a timerexpires, etc.

In response to determining that a dead reckoning position estimate valueis available (i.e., determination block 1506=“Yes”), the mobile devicemay determine, compute, or calculate an error value (e.g., in the formof a variance, etc.) that identifies the error associated with thedetermined local-position or dead reckoning estimate value in block1508. In determination block 1510, the mobile device may determinewhether a combined sensor position estimate value is available (e.g., isdeterminable from information collect from sensors or stored in memory,etc.) for the current time. In some embodiments, the mobile device maybe configured to calculate/determine the inputs for computing ordetermining the combined sensor position estimate value by filtering theoutput of environmental sensors, such as the accelerometer, barometer,gyro, magnetometer and/or thermometer, and using the filtered sensoroutputs as the inputs to an algorithm or method for computing thecombined sensor position estimate value. In some embodiments, in block1510, the mobile device may execute or perform a single variable kalmanfilter using the combined or “fused” sensor outputs to obtain,determine, or compute the combined sensor position estimate value. Thesingle variable kalman filter may be a procedure, algorithm, method,technique, or sequence of operations for accomplishing the function of akalman filter.

In response to determining that combined sensor position estimate is notavailable for the current time (i.e., determination block 1510 equals,or evaluates to, “No”), the mobile device may determine, compute, orcalculate an error value (e.g., in the form of a variance value, etc.)that identifies an error/variance associated with the external positionestimate in block 1512. For example, in block 1512, the mobile devicemay extrapolate the last available combined sensor position estimatevalue to fit a time stamp established or determined by the deadreckoning module of the mobile device. In some embodiments, the mobiledevice may be configured to increase or increment the error/variancevalue associated with the combined sensor position estimate value so asto compensate for a potential inaccuracy of the calculation. Saidanother way, the mobile device may be configured to update the combinedsensor position estimate error value in block 1512 to better account forpotential inaccuracies in its computations or location/positiondeterminations.

In response to determining that combined sensor position estimate valueis available for the current time (i.e., determination block 1510equals, or evaluates to, “Yes”), the mobile device may determine anerror/variance value for the external position estimate value in block1514. Said another, in block 1514 the mobile device may determine,compute, or calculate an external position estimate error value inresponse to determining that a combined sensor position estimate valueis available.

In determination block 1516, the mobile device may determine whether atrilateration position estimate value for a current time is available.As described above, the mobile device may obtain more accurate positioninformation by calculating its own location based on the distancebetween the mobile device and three or more reference locations. Someembodiments may include obtaining distance information from severalreference locations and executing a kalman filter on the obtainedcoordinates to produce a single estimate of position, velocity, andacceleration in block 1516. In response to determining that atrilateration position estimate value for the current time is notavailable (i.e., determination block 1516 equals or evaluates to “No”),in block 1518 the mobile device may extrapolate the last availabletrilateration location information to a current time stamp establishedby the dead reckoning module. In response to determining that thetrilateration position estimate value for the current time is available(i.e., determination block 1516 equals or evaluates to “Yes”), themobile device may determine the error/variance associated with thetrilateration position estimate value in block 1520.

In block 1522, the mobile device may compute, calculate, or determine afinal location estimate value based on the dead reckoning positionestimate value, the combined sensor position estimate value, thetrilateration position estimate value, and the location informationreceived from external systems (e.g., GPS coordinates, etc.). In variousembodiments, the mobile device may set the values of one or more fieldsin the final location estimate value to be equal to the product ofexecuting a kalman filter on the sets of location information/values,which may include (or may be based on) a position informationestimate/value, velocity information estimate/value, and an accelerationinformation estimate/value. In block 1524, the mobile device may updatethe a final location estimate value with the calculated estimate/valuesand/or calculate or determine a gain value.

In block 1526, the mobile device may wait for a pre-determined amount oftime (or wait until a time interval lapses) return to block 1516 torepeat the operations of method 1500 to begin updating the locationinformation for the current time. In some embodiments, the time intervalmay be synched to the time of the dead reckoning module. Thus eachsubsequent updating of the dead reckoning location information mayrepresent the beginning of another final location informationrecalculation.

FIGS. 16A-16B illustrate embodiment mobile device methods 1600 forcalculating location information estimates. The operations of method1600 may be performed by a processor or processing core in a mobiledevice 102.

With reference to FIG. 16A, an embodiment method for implementing atrilateration technique may include the execution of a kalman filter ondistance information to produce a more accurate location, velocity, andacceleration estimate. In block 1602 the mobile device may initialize astarting point in the same manner as described with reference to block1502 of FIG. 15. In block 1604, the mobile device may receive locationinformation from three or more reference locations (e.g., other mobiledevices, access points, etc.) and may calculate a distance between themobile device and each of the reference locations. The mobile device mayfurther calculate a velocity and acceleration of the mobile device withrespect to each of the reference locations. In block 1606, the mobiledevice may check for the presence of received inputs from at least threeseparate reference locations. If the mobile device has received locationinformation from at least three reference locations then the process mayproceed to block 1610. If the mobile device has not received asufficient number of inputs from the reference locations, it may inblock 1608 wait to receive further input. In some embodiments, while themobile device waits for additional reference location information, itmay update previous trilateration information according to theembodiment method 1700 described below with reference to FIG. 17.

In block 1610, the mobile device may calculate an error or varianceassociated with the distance calculation. In block 1612, the calculateddistance information, along with the associated velocities andacceleration calculations may be separated into their directionalcomponents and grouped into vectors with like components from eachreference location. For example, the calculations may be separated intoCartesian or radial coordinate components, and a z component vector maycontain the z components of the distance, velocity, and accelerationinformation for all location information received from the at leastthree reference locations. In blocks 1614, 1616, and 1618, a kalmanfilter may be executed on each of the component vectors. In block 1620,the component vectors of all the kalman filter functions may be combinedto calculate a three dimensional position estimate in the mannerdescribed with reference to embodiment method 1800 and FIG. 18.

In block 1622, the processor of the mobile device may update thetrilateration position information with the estimate calculated in block1620, and may further calculate a process gain. In block 1624, themobile device may wait a predetermined interval of time, as establishedby the time stamp of the dead reckoning module, and may then return toblock 1604, to begin updating the trilateration location information.

FIG. 16B illustrates an embodiment mobile device method for calculatinglocation estimates and proceeds in the manner described with referenceto FIG. 16A above, but does not receive information from referencelocations. In block 1602, the mobile device may initialize a startingposition for the combined sensor location information calculation. Inblock 1630 the mobile device may collect data generated by local sensorssuch as an accelerometer, barometer, gyro, magnetometer and thermometer.The various sensor outputs may include position, velocity, andacceleration information and may be utilized by the mobile device in thesame manner as the trilateration inputs. In blocks 1606 through 1624,the method may proceed as described above with respect to steps 1606through 1624 of FIG. 16A. In some embodiments, the combined sensorlocation information may be used as input for dead reckoning.

FIG. 17 illustrates an embodiment mobile device method for updatinglocation information. From block 1608 of embodiment method 1600, theremay be a lack of sufficient input for a given time interval to permitaccurate location calculation. In block 1702, the mobile device mayextrapolate a previous set of location information (e.g., position,velocity, and acceleration information) to a current time interval and.The error associated with the calculation may be increased in block1704. The resulting location information and adjusted error may bereturned to block 1604 for use in determining an updated set of locationinformation.

FIG. 18, illustrates an embodiment mobile device method of executing arecursive, linear filter on location information. Using an initializedstarting position, the filter may generate a new state estimate bycombining new measurements with a predicted state estimate based on themeasurements of a preceding time interval. At each iteration, locationestimates are produced using only the new set of measurement vectors andvalues stored from the previous cycle. In some embodiments, the statethree measurements for each input may be stored to facilitatecalculation of a three dimensional position. Through multiple iterationsof the filter, process noise, such as less accurate location informationis removed from the produced final location estimate.

During the filter process, the state estimate “L” may be considered tobe current for a time “k” or predicted for a time “k−.” The state, orlocation estimate may be a nine element vector including an estimatedposition, velocity, and acceleration for each coordinate component of acoordinate system. For example, a location estimate for a Cartesiancoordinate system may be represented by the expression

L _(k) =[x,y,z,v _(x) ,v _(y) ,v _(z) ,a _(x) ,a _(y) ,a _(z)]

In various embodiments, the vector may be separated into multiplesmaller vectors including all elements associated with a coordinatecomponent, thereby enabling easy isolation of position, velocity, andacceleration information with respect to a single axis of translation.Thus, “L_(k)” may e represented by the series of expression:

L _(xk) =[x,v _(x) ,a _(x)]

L _(yk) =[y,v _(y) ,a _(y)]

L _(zk) =[z,v _(z) ,a _(z)]

The current state “L_(k)” may depend only on the predicted state for theprevious time interval, new input measurements “G” (e.g., a new locationinformation input), a transition matrix “H” and the kalman gain “K.”Thus, the current location estimate may be represented by the function:

L _(k) =L _(k) ⁻ +K _(k)(G _(k) −H·L _(k) ⁻)

To begin location estimate calculation, a starting position “L₀” andassociated covariance “P₀” may be initialized using GPS coordinates orlocal sensor output for a position, velocity, and acceleration. Theestimated covariance matrix “P” may comprise the variance of an Lvectoralong the diagonal and the off diagonal elements set to zero. If nosensor output location information or externally provided startingcoordinates are available, the initial values may be set at either 0 oran estimated distance using RSSI and or Time of Flight (TOF) from areference location (e.g., another mobile device), such that 0.5 of theestimated distance will be applied to the X and Y component of thereporting reference location and the altitude, Z, will use as thatreported by the other reference locations.

In block 1802 an error or covariance P may be determined, along withweight factors. Block 1802 may be the end of the prediction phase of thekalman filter process and may pass a predicted location, covariance, andweights to block 1804, the beginning of the updating phase. Once thestarting point is initialized the starting position may be used as apredicted measurement and may be represented by the function:

L _(k) =AL _(k-1) +Bu _(k) +w _(k-1)

Where “A” and “B” are state transition matrices that may map a statefrom a time “k−1” to “k. The parameter w_(k-1) is a vector of elementsrepresenting the uncertainty in the noise for each of the parameters inthe state vector L, and “u_(k)” is a parameter nulled out duringcalculation. The mean noise “w” along with a standard deviation of thenoise “v_(k)” may enable convergence of location and sensor input datum,which are non-Gaussian. Current measurements “G” may be expressed as afunction of the standard deviation by “G_(k)=HL_(k)+v_(k)” andalternatively as “G_(k)=H·L_(k)+R” where “R” is a matrix representingthe variance of the measurements. The estimated covariance may berepresented in terms of a previous covariance estimate, the transitionmatrix A, and a covariance matrix “Q” and expressed by the function:

P _(k) ⁻ =AP _(k-1) A ^(T) +Q

In block 1804, updating phase may begin, and the location estimate “L”may be updated. This phase ay begin by computing the Kalman gain “K” forthe current time interval. The gain may be a product of the estimatedcovariance, and the measurement variance “R,” and may thus berepresented by the expression:

K _(k) =P _(k) ⁻ ·H ^(T)·(H·P _(k) ⁻ ·H ^(T) +R)⁻¹

The current location estimate may be updated using the current locationestimate expression. Kalman gain depends on the current state estimateand the accuracy of the measurements. As the accuracy of themeasurements increase the Kalman gain will be high placing higher weighton the measurements. In some embodiments, the time k may be larger, thusdecreasing the accuracy of the measurements (due to staleness of themeasurement) resulting in a low Kalman gain placing more weight onprediction than on the measurements. With a high gain, more weight willbe placed on measurements than on the predicted value. In block 1806,the current covariance “P” may be computed. Over multiple iterations ofthe filter, the off-diagonal elements of the covariance matrix maybecome non-zero elements. The current process covariance may beexpressed by the function:

P _(k)=(1−K _(k) H)·P _(k) ⁻

The current location “L” and a current process covariance matrix P maybe the outputs of the updating phase and may be passed as input to thebeginning of the prediction phase in block 1808 for the next iterationof the filter. In block 1808, the mobile device may predict the locationmatrix/matrices and process covariance “P” matrix for a time “k+1” mayand pass them as input to the second step of the predicting phase inblock 1802. The current location estimate may also be used as currentposition, velocity, and acceleration information for location basedservices, and may be passed to the network in accordance with variousembodiments. In some embodiments, the current location estimate may bepassed as input to a second kalman filter and combined with otherlocation inputs to produce a final location estimate.

In various embodiments, the systems, methods, and devices may execute akalman filter in three separate instances within the embodiment method1500 described with reference to FIG. 15. These instances may includeexecution of a kalman filter on the combined sensor locationinformation, the trilateration location information, and the finallocation estimate, which combines the sensor location information,trilateration location information, and all other location inputsources. For each instance, the inputs must be synchronized with thetime stamp used by the dead reckoning module and may be extrapolated tofit a current dead reckoning time.

In various embodiments, the mobile device may utilize a kalman filterprocess to determine accurate location information for a mobile device.Multiple kalman filters may be executed on location information fromvaried sources. The output of filtering location information frommultiple sources may be input for a final stage kalman filter processthat may reduce the noise of inaccurate location information byrecursively combining and estimating the combination of locationinformation from different sources to produce a final location estimate.

The various embodiments may be implemented on a variety of mobilecomputing devices, an example of which is illustrated in FIG. 19.Specifically, FIG. 19 is a system block diagram of a mobile transceiverdevice in the form of a smartphone/cell phone 1900 suitable for use withany of the embodiments. The cell phone 1900 may include a processor 1901coupled to internal memory 1902, a display 1903, and to a speaker 1954.Additionally, the cell phone 1900 may include an antenna 1904 forsending and receiving electromagnetic radiation that may be connected toa wireless data link and/or cellular telephone transceiver 1905 coupledto the processor 1901. Cell phones 1900 typically also include menuselection buttons or rocker switches 1908 for receiving user inputs.

A typical cell phone 1900 also includes a sound encoding/decoding(CODEC) circuit 1924 which digitizes sound received from a microphoneinto data packets suitable for wireless transmission and decodesreceived sound data packets to generate analog signals that are providedto the speaker 1954 to generate sound. Also, one or more of theprocessor 1901, wireless transceiver 1905 and CODEC 1924 may include adigital signal processor (DSP) circuit (not shown separately). The cellphone 1900 may further include a peanut or a ZigBee transceiver (i.e.,an IEEE 802.15.4 transceiver) 1913 for low-power short-rangecommunications between wireless devices, or other similar communicationcircuitry (e.g., circuitry implementing the Bluetooth® or WiFiprotocols, etc.).

Various embodiments may be implemented on any of a variety ofcommercially available server devices, such as the server 2100illustrated in FIG. 20. Such a server 2000 typically includes one ormore processors 2001, 2002 coupled to volatile memory 2003 and a largecapacity nonvolatile memory, such as a disk drive 2004. The server 2000may also include a floppy disc drive, compact disc (CD) or DVD discdrive 2006 coupled to the processor 2001. The server 2000 may alsoinclude network access ports 2006 coupled to the processor 2001 forestablishing data connections with a network 2005, such as a local areanetwork coupled to other communication system computers and servers.

The processors 1901, 2001, and 2002 may be any programmablemicroprocessor, microcomputer or multiple processor chip or chips thatcan be configured by software instructions (applications) to perform avariety of functions, including the functions of the various embodimentsdescribed below. In some mobile devices, multicore processors 2002 maybe provided, such as one processor core dedicated to wirelesscommunication functions and one processor core dedicated to runningother applications. Typically, software applications may be stored inthe internal memory 1902, 2003, and 2004 before they are accessed andloaded into the processor 1901, 2001, and 2002. The processor 1901,2001, and 2002 may include internal memory sufficient to store theapplication software instructions.

The wireless device location determination techniques described hereinmay be implemented in conjunction with various wireless communicationnetworks such as a wireless wide area network (WWAN), a wireless localarea network (WLAN), a wireless personal area network (WPAN), and so on.The term “network” and “system” are often used interchangeably. A WWANmay be a Code Division Multiple Access (CDMA) network, a FrequencyDivision Multiple Access (FDMA) network, a Time Division Multiple Access(TDMA) network, an OFDMA network, a 3GPP LTE network, a WiMAX (IEEE802.16) network, and so on. A CDMA network may implement one or moreradio access technologies (RATs) such as CDMA2000, Wideband-CDMA(W-CDMA), and so on. CDMA2000 includes IS-95, IS-2000, and IS-856standards. W-CDMA is described in documents from a consortium named “3rdGeneration Partnership Project” (3GPP). CDMA2000 is described indocuments from a consortium named “3rd Generation Partnership Project 2”(3GPP2). 3GPP and 3GPP2 documents are publicly available. A WLAN may bean IEEE 802.11x network, and a WPAN may be a Bluetooth network, an IEEE802.15x, or some other type of network. The techniques may also beimplemented in conjunction with any combination of WWAN, WLAN, and/orWPAN.

The various embodiments may include enhancements to the current locationbased service methodologies used for wireless mobile communications.Determining the location of the mobile device in a wireless network isbecoming more and more important in recent years both for commercial andpublic safety positioning applications. Services and applications basedon accurate knowledge of the location of a mobile device are becomingmore prevalent in the current and future wireless communication systemsAdditionally Public Safety is also embarking on the use of commercialcellular technology, LTE, as a communication protocol of choice. Ofspecific importance is the need for improved situation awareness at anincident with first responders.

Presently GPS provides a good estimate of the mobile devices currentlocation under optimum conditions. However in many situations andespecially in building and urban environments the ability to utilize GPSfor position location determination is hampered and many times is notusable. The network based solutions for determining the mobile deviceslocation, while good, has many problems with locating the mobile devicewithin buildings and in urban areas. The introduction of wirelessnetwork systems such as the third generation partnership project (3GPP)long-term evolution (LTE) present new capabilities has the ability inthe public safety band to provide excellent coverage in urban and indoorenvironments. Although the wireless mobile networks can provide coveragein urban and in-building environments the location information positionaccuracy has limitations.

Better positional location accuracy and confidence has many advantagesfor use in emergency location services, commercial location services,internal location services and lawful intercept location services. Thevarious embodiments provide the ability to improve the positionallocation information for both new and existing wireless networks.

For commercial applications the ability to have the mobile deviceimprove location specific information within a multiple story building,in an urban environment or within a mall provides both network radioresource improvements and has unique advertising targeting capabilitiesas well as applications for improved fleet management, asset trackingand various machine to machine communications applications wherepositional determination is required to be highly accurate. Forcommercial users the need for improves position location informationaccuracy is most needed for in-building environments where the locationof the mobile device can be more accurately pin pointed for locationbased services

The advantage of law enforcement with improved positional informationwill enable the tracking of mobile devices inside a building to enabledetermination of what floor or part of the building the device is beingused is located without the need for replacing radio beacons or locationaware access points.

For emergency services the advantage comes to better positional locationof the part in need of assistance especially in an urban environmentwhere the positional information is most problematic with existingtechniques.

For first responders this enhancement enables mobile devices which arein the same scene to help augment their position coordinates with eachother in a controlled ad-hoc environment. The positional informationshared not only includes latitude and longitude but also altitude andvelocity. Since this information involves a small amount of data themobile devices can have the E-SMLC in the case of LTE share theinformation both on net and off-net.

The use of sensors including accelerometers, gyroscopes, magnetometersand pressure sensors along with GPS receivers with mobile devices isbecoming more prevalent. Therefore the enhancements for positionallocation will give the E-SMLC in the case of LTE the ability to not onlyutilize GPS or Network derived coordinate information but also to havean augmentation with sensors associated the mobile device which caninclude accelerometers, gyroscopes, magnetometer and pressure sensorsfor refining and reducing some of the positional uncertainties that arein inherent to wireless positional determination.

Wireless mobile network like LTE the position location informationaccuracy needs to be improved for in building environments in additionto providing more accurate location information about where the mobiledevices are actually located. Whether the mobile device is used by afirst responder, commercial cellular user or a combination of both.

Positional location improvement enable improved situation awareness,improved telemetry, and improved overall communication with the incidentcommander. In addition, the mobile devices proximity location to othermobile devices can and will change dynamically allowing for resources tobe added and/or reassigned as the need arises for operationalrequirements.

The foregoing method descriptions and the process flow diagrams areprovided merely as illustrative examples and are not intended to requireor imply that the blocks of the various embodiments must be performed inthe order presented. As will be appreciated by one of skill in the artthe order of blocks in the foregoing embodiments may be performed in anyorder. Words such as “thereafter,” “then,” “next,” etc. are not intendedto limit the order of the blocks; these words are simply used to guidethe reader through the description of the methods. Further, anyreference to claim elements in the singular, for example, using thearticles “a,” “an” or “the” is not to be construed as limiting theelement to the singular.

The various illustrative logical blocks, modules, circuits, andalgorithm blocks described in connection with the embodiments disclosedherein may be implemented as electronic hardware, computer software, orcombinations of both. To clearly illustrate this interchangeability ofhardware and software, various illustrative components, blocks, modules,circuits, and blocks have been described above generally in terms oftheir functionality. Whether such functionality is implemented ashardware or software depends upon the particular application and designconstraints imposed on the overall system. Skilled artisans mayimplement the described functionality in varying ways for eachparticular application, but such implementation decisions should not beinterpreted as causing a departure from the scope of the presentinvention.

The hardware used to implement the various illustrative logics, logicalblocks, modules, and circuits described in connection with theembodiments disclosed herein may be implemented or performed with ageneral purpose processor, a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA) or other programmable logic device, discrete gate ortransistor logic, discrete hardware components, or any combinationthereof designed to perform the functions described herein. Ageneral-purpose processor may be a microprocessor, but, in thealternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration. Alternatively, some blocks or methods may be performed bycircuitry that is specific to a given function.

In one or more exemplary aspects, the functions described may beimplemented in hardware, software, firmware, or any combination thereof.If implemented in software, the functions may be stored as one or moreinstructions or code on a non-transitory computer-readable medium ornon-transitory processor-readable medium. The steps of a method oralgorithm disclosed herein may be embodied in a processor-executablesoftware module which may reside on a non-transitory computer-readableor processor-readable storage medium. Non-transitory computer-readableor processor-readable storage media may be any storage media that may beaccessed by a computer or a processor. By way of example but notlimitation, such non-transitory computer-readable or processor-readablemedia may include RAM, ROM, EEPROM, FLASH memory, CD-ROM or otheroptical disk storage, magnetic disk storage or other magnetic storagedevices, or any other medium that may be used to store desired programcode in the form of instructions or data structures and that may beaccessed by a computer. Disk and disc, as used herein, includes compactdisc (CD), laser disc, optical disc, digital versatile disc (DVD),floppy disk, and blu-ray disc where disks usually reproduce datamagnetically, while discs reproduce data optically with lasers.Combinations of the above are also included within the scope ofnon-transitory computer-readable and processor-readable media.Additionally, the operations of a method or algorithm may reside as oneor any combination or set of codes and/or instructions on anon-transitory processor-readable medium and/or computer-readablemedium, which may be incorporated into a computer program product.

The preceding description of the disclosed embodiments is provided toenable any person skilled in the art to make or use the presentinvention. Various modifications to these embodiments will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to other embodiments without departing from thespirit or scope of the invention. Thus, the present invention is notintended to be limited to the embodiments shown herein but is to beaccorded the widest scope consistent with the following claims and theprinciples and novel features disclosed herein.

What is claimed is:
 1. A method of providing an enhanced location basedservice via a mobile device, including: determining, by a processor ofthe mobile device, an initial position of the mobile device; generatinglocal position information; generating external position informationbased on location information received from an external locationtracking system; generating proximity position information based ondistance information received from a second mobile device; generatingfinal location information based on the determined initial position, thegenerated local position information, the generated external positioninformation, and the generated proximity position information; and usingthe generated final location information to provide a location basedservice.
 2. The method of claim 1, wherein generating the final locationinformation based on the determined initial position, the generatedlocal position information, the generated external position information,and the generated proximity position information comprises: generating aposition information set, a velocity information set, and anacceleration information set, each of which include a latitudecomponent, a longitude component, and an altitude component.
 3. Themethod of claim 2, wherein generating any of the local positioninformation, the external position information, or the proximityposition information further comprises: separating location informationinto a set of latitude components, a set of longitude components, and aset of altitude components; and executing a kalman filter on each of theset of latitude components, the set of longitude components, and the setof altitude components to produce position information.
 4. The method ofclaim 3, further comprising determining an error associated withgeneration of the position information.
 5. The method of claim 1,further comprising: updating the local position information after afirst time interval to produce updated local position information;updating the external position information after a second time intervalto produce updated external position information; and updating theproximity position information after a third time interval to produceupdated proximity position information.
 6. The method of claim 5,further comprising: updating the generated final location informationbased on the updated local position information, the updated externalposition information, the updated proximity position information and thegenerated final location information to produce an updated finallocation estimation set.
 7. The method of claim 5, wherein updating anyof the local position information, the external position information, orthe proximity position information comprises: determining whetherupdated location information or updated distance information isavailable; combining current location information or current distanceinformation with an error value, in response to determining that updatedlocation information or updated distance information is not available.8. The method of claim 5, wherein the first time interval, the secondtime interval, or the third time interval is a time interval betweensuccessive determinations of the local position information.
 9. Themethod of claim 1, wherein the distance information comprises a distancefrom the mobile device to the second mobile device.
 10. The method ofclaim 1, wherein the local position information is obtained using deadreckoning.
 11. The method of claim 1, wherein the local positioninformation is obtained using combination of local sensor outputs. 12.The method of claim 1, wherein the external location tracking systemcomprise a global positioning (GPS).
 13. A mobile device comprising: anantenna; one or more processors or processor cores configured withprocessor-executable instructions to perform operations comprising:determining an initial position of the mobile device; generating localposition information; generating external position information based onlocation information received from an external location tracking systemand generating proximity position information based on distanceinformation received via the antenna from a second mobile device;generating final location information based on the determined initialposition, the generated local position information, the generatedexternal position information, and the generated proximity positioninformation; and using the generated final location information toprovide a location based service.
 14. The mobile device of claim 13,wherein the one or more processors or processor cores is furtherconfigured with processor-executable instructions to perform operationscomprising such that generating the final location information comprisesgenerating a position information set, a velocity information set, andan acceleration information set, each of which include a latitudecomponent, a longitude component, and an altitude component.
 15. Themobile device of claim 14, wherein the one or more processors orprocessor cores is further configured with processor-executableinstructions to perform operations comprising such that generating anyof the local position information, the external position information, orproximity position information further comprises: separating locationinformation into a set of latitude components, a set of longitudecomponents, and a set of altitude components; and executing a kalmanfilter on each of the set of latitude components, the set of longitudecomponents, and the set of altitude components to produce positioninformation.
 16. The mobile device of claim 15, wherein the one or moreprocessors or processor cores is further configured withprocessor-executable instructions to perform operations comprising:determining an error associated with generation of the positioninformation.
 17. The mobile device of claim 13, wherein the one or moreprocessors or processor cores is further configured withprocessor-executable instructions to perform operations furthercomprising: updating the local position information after a first timeinterval to produce updated local position information; updating theexternal position information after a second time interval to produceupdated external position information; and updating the proximityposition information after a third time interval to produce updatedproximity position information.
 18. The mobile device of claim 17,wherein the one or more processors or processor cores is furtherconfigured with processor-executable instructions to perform operationscomprising: updating the generated final location information based onthe updated local position information, the updated external positioninformation, the updated proximity position information and thegenerated final location information to produce an updated finallocation information.
 19. The mobile device of claim 17, wherein the oneor more processors or processor cores is further configured withprocessor-executable instructions to perform operations comprising suchthat updating any of the local position information, the externalposition information, or the proximity position information comprises:determining whether updated location information or updated distanceinformation is available; combining current location information orcurrent distance information with an error value, in response todetermining that updated location information or updated distanceinformation is not available.
 20. The mobile device of claim 17, whereinthe one or more processors or processor cores is further configured withprocessor-executable instructions to perform operations comprising suchthat the first time interval, the second time interval, or the thirdtime interval is a time interval between successive determinations ofthe local position information.
 21. The mobile device of claim 13,wherein the one or more processors or processor cores is furtherconfigured with processor-executable instructions to perform operationscomprising such that the distance information comprises a distance fromthe mobile device to the second mobile device.
 22. The mobile device ofclaim 13, wherein the one or more processors or processor cores isfurther configured with processor-executable instructions to performoperations comprising such that local position information is obtainedusing dead reckoning.
 23. The mobile device of claim 13, wherein the oneor more processors or processor cores is further configured withprocessor-executable instructions to perform operations comprising suchthat the local position information is obtained using combination oflocal sensor outputs.
 24. The mobile device of claim 13, wherein the oneor more processors or processor cores is further configured withprocessor-executable instructions to perform operations comprising suchthat the external location tracking system comprise a global positioning(GPS).
 25. A non-transitory processor-readable medium having storedthereon processor-executable software instructions to cause a processorof a mobile device to perform operations comprising: determining aninitial position of the mobile device; generating local positioninformation; generating external position information based on locationinformation received from an external location tracking system andgenerating proximity position information based on distance informationreceived via an antenna, from a second mobile device; generating finallocation information based on the determined initial position, thegenerated local position information, the generated external positioninformation, and the generated proximity position information; and usingthe generated final location information to provide a location basedservice.
 26. The non-transitory processor-readable medium of claim 25,wherein the stored processor-executable instructions are configured tocause a processor to perform operations such that generating the finallocation information comprises generating a position information set, avelocity information set, and an acceleration information set, each ofwhich include a latitude component, a longitude component, and analtitude component.
 27. The non-transitory processor-readable medium ofclaim 26, wherein the stored processor-executable instructions areconfigured to cause a processor to perform operations such thatgenerating any of the local position information, the external positioninformation, or the proximity position information further comprises:separating location information into a set of latitude components, a setof longitude components, and a set of altitude components; and executinga kalman filter on each of the set of latitude components, the set oflongitude components, and the set of altitude components to produceposition information.
 28. The non-transitory processor-readable mediumof claim 27, wherein the stored processor-executable instructions areconfigured to cause a processor to perform operations furthercomprising: determining an error associated with generation of theposition information.
 29. The non-transitory processor-readable mediumof claim 25, wherein the stored processor-executable instructions areconfigured to cause a processor to perform operations such that:updating the local position information after a first time interval toproduce updated local position information; updating the externalposition information after a second time interval to produce updatedexternal position information; and updating the proximity positioninformation after a third time interval to produce updated proximityposition information.
 30. The non-transitory processor-readable mediumof claim 29, wherein the stored processor-executable instructions areconfigured to cause a processor to perform operations such that:updating the generated final location information based on the updatedlocal position information, the updated external position information,the updated proximity position information and the generated finallocation information to produce an updated final location information.31. The non-transitory processor-readable medium of claim 30, whereinthe stored processor-executable instructions are configured to cause aprocessor to perform operations such that updating any of the localposition information, the external position information, or theproximity position information comprises: determining if updatedlocation information or updated distance information is available;combining current location information or current distance informationwith an error value, in response to determining that updated locationinformation or updated distance information is not available.
 32. Thenon-transitory processor-readable medium of claim 30, wherein the storedprocessor-executable instructions are configured to cause a processor toperform operations such that the first time interval, the second timeinterval, or the third time interval is a time interval betweensuccessive determinations of the local position information.
 33. Thenon-transitory processor-readable medium of claim 25, wherein the storedprocessor-executable instructions are configured to cause a processor toperform operations such that the distance information comprisesinformation identifying a distance from the mobile device to the secondmobile device.
 34. The non-transitory processor-readable medium of claim25, wherein the stored processor-executable instructions are configuredto cause a processor to perform operations such that the local positioninformation is obtained using dead reckoning.
 35. The non-transitoryprocessor-readable medium of claim 25, wherein the storedprocessor-executable instructions are configured to cause a processor toperform operations such that the local position information is obtainedusing combination of local sensor outputs.
 36. The non-transitoryprocessor-readable medium of claim 25, wherein the storedprocessor-executable instructions are configured to cause a processor toperform operations such that receiving external information from theexternal location tracking system comprises receiving externalinformation from a global positioning (GPS).